From bcfa2d0ba89c802e6088b8c214c638a112428d1a Mon Sep 17 00:00:00 2001 From: cianc Date: Wed, 17 Sep 2025 10:05:32 +0100 Subject: [PATCH 1/2] Fix some typos and sphinx warnings. A few small typos, sphinx warnings about too-short underlines, duplicate anchors and incorrent sublist indentation. --- docs/_sources/advanced_installation.rst.txt | 10 ++-- docs/_sources/comet.rst.txt | 4 +- docs/_sources/faq.rst.txt | 6 +- docs/_sources/installation.rst.txt | 4 +- docs/_sources/methodology.rst.txt | 42 ++++++------- docs/_sources/model_examples.rst.txt | 2 +- docs/_sources/parameters.rst.txt | 16 ++--- docs/_sources/usage.rst.txt | 2 +- docs/advanced_installation.html | 2 +- docs/edit/advanced_installation.rst | 10 ++-- docs/edit/comet.rst | 4 +- docs/edit/faq.rst | 6 +- docs/edit/installation.rst | 4 +- docs/edit/methodology.rst | 42 ++++++------- docs/edit/model_examples.rst | 2 +- docs/edit/parameters.rst | 16 ++--- docs/edit/usage.rst | 2 +- docs/faq.html | 6 +- docs/methodology.html | 65 +++++++++++---------- docs/model_examples.html | 2 +- docs/parameters.html | 28 ++++----- docs/searchindex.js | 6 +- docs/usage.html | 2 +- 23 files changed, 146 insertions(+), 137 deletions(-) diff --git a/docs/_sources/advanced_installation.rst.txt b/docs/_sources/advanced_installation.rst.txt index 130d4060c..3c89dcf26 100644 --- a/docs/_sources/advanced_installation.rst.txt +++ b/docs/_sources/advanced_installation.rst.txt @@ -122,7 +122,7 @@ This section describes how to deploy CodeCarbon as a system service using Ansibl It automate the manual installation done in the previous chapter. What the Playbook Does --------------------- +---------------------- The Ansible playbook automates the following tasks: * Creates a dedicated system user and group for CodeCarbon @@ -134,14 +134,14 @@ The Ansible playbook automates the following tasks: * Starts and enables the service Prerequisites ------------- +------------- * Ansible installed on your machine * Debian-based target system(s) * SSH access to target system(s) * CodeCarbon API credentials from the dashboard Directory Structure ------------------ +------------------- .. code-block:: text codecarbon/deploy/ansible/codecarbon_cli_as_a_service/ @@ -158,11 +158,11 @@ Directory Structure └── main.yml Quick Start ----------- +----------- 1. Set the the target to install in ``hosts``: - .. code-block:: txt + .. code-block:: text yourservername.yourdomain.com hostname=yourservername ansible_user=root ansible_ssh_private_key_file=~/.ssh/id_ed25519 diff --git a/docs/_sources/comet.rst.txt b/docs/_sources/comet.rst.txt index 7219e9bee..b1ac48f4a 100644 --- a/docs/_sources/comet.rst.txt +++ b/docs/_sources/comet.rst.txt @@ -4,7 +4,7 @@ Comet Integration =========================== -CodeCarbon can be automatically integrated with `Comet `_ for experiment tracking and visualization. Comet provides data scientists with powerful tools to track, compare, explain, and reproduce their experiments. Now, with CodeCarbon you can easily track the carbon footprint of your jobs along with your training metrics, hyperparameters, dataset samples, artifacts, and more. +CodeCarbon can be automatically integrated with `Comet `__ for experiment tracking and visualization. Comet provides data scientists with powerful tools to track, compare, explain, and reproduce their experiments. Now, with CodeCarbon you can easily track the carbon footprint of your jobs along with your training metrics, hyperparameters, dataset samples, artifacts, and more. .. image:: ./images/comet-workspace.png :align: center @@ -19,7 +19,7 @@ To get started with the Comet-CodeCarbon integration, make sure you have comet-m pip install comet_ml>=3.2.2 -Go to `Comet's website `_ and create a free account. From your account settings page, copy your personal API key. +Go to `Comet's website `__ and create a free account. From your account settings page, copy your personal API key. In the `mnist-comet.py `_ example file, replace the placeholder code with your API key: diff --git a/docs/_sources/faq.rst.txt b/docs/_sources/faq.rst.txt index 220559248..b6fe5977e 100644 --- a/docs/_sources/faq.rst.txt +++ b/docs/_sources/faq.rst.txt @@ -22,9 +22,9 @@ Frequently Asked Questions - When available we use data from `ourworld in data `_ - - if not available we use the electricity mix of the country find on `globalpetrolprices.com `_ that we multiply by the carbon intensity of the source of electricity (`that you can find here `_) + - If not available we use the electricity mix of the country find on `globalpetrolprices.com `_ that we multiply by the carbon intensity of the source of electricity (`that you can find here `_) - - if we have neither we default to a world average of 475 gCO2.eq/KWh from `IEA `_. + - If we have neither we default to a world average of 475 gCO2.eq/KWh from `IEA `_. * **How do I offset my emissions?** @@ -32,6 +32,6 @@ Frequently Asked Questions * **How can I help?** - If you find a functionality missing in the CodeCarbon repo, please `open an issue `_ so that you (and others!) can help add it. We did our best to cover all use cases and options, but we count on the open source community to help make the package an even greater success. + If you find any functionality missing in the CodeCarbon repo, please `open an issue `_ so that you (and others!) can help add it. We did our best to cover all use cases and options, but we count on the open source community to help make the package an even greater success. diff --git a/docs/_sources/installation.rst.txt b/docs/_sources/installation.rst.txt index 0e5cf619f..a46efccfd 100644 --- a/docs/_sources/installation.rst.txt +++ b/docs/_sources/installation.rst.txt @@ -15,7 +15,7 @@ For installing conda, follow the instructions on the From PyPi repository -------------------- -The package is hosted on the pip repository `here `_. +The package is hosted on the pip repository `here `__. To install the package, run the following command in your terminal. @@ -26,7 +26,7 @@ To install the package, run the following command in your terminal. From conda repository --------------------- -The package is hosted on the conda repository `here `_. +The package is hosted on the conda repository `here `__. To install the package, run the following command in your terminal. diff --git a/docs/_sources/methodology.rst.txt b/docs/_sources/methodology.rst.txt index f235923f1..56142cb91 100644 --- a/docs/_sources/methodology.rst.txt +++ b/docs/_sources/methodology.rst.txt @@ -24,7 +24,7 @@ energy sources that are used to generate electricity, including fossil fuels and :height: 300px :width: 350px -When available, CodeCarbon uses global carbon intensity of electricity per cloud provider ( `here `_ ) or per country ( `here `_ ). +When available, CodeCarbon uses global carbon intensity of electricity per cloud provider ( `here `__) or per country ( `here `__ ). If we don't have the global carbon intensity or electricity of a country, but we have its electricity mix, we used to compute the carbon intensity of electricity using this table: @@ -63,9 +63,9 @@ Then, for example, if the Energy Mix of the Grid Electricity is 25% Coal, 35% Pe Net Carbon Intensity = 0.25 * 995 + 0.35 * 816 + 0.26 * 743 + 0.14 * 29 = 731.59 kgCO₂/kWh -But it doesn't happen anymore because Our World in Data now provides the global carbon intensity of electricity per country ( `source `_ ). Some countries are missing data for last year, so we use the previous year data available. +But it doesn't happen anymore because Our World in Data now provides the global carbon intensity of electricity per country ( `source `__ ). Some countries are missing data for last year, so we use the previous year data available. -If ever we have neither the global carbon intensity of a country nor it's electricity mix, we apply a world average of 475 gCO2.eq/KWh ( `source `_ ). +If ever we have neither the global carbon intensity of a country nor it's electricity mix, we apply a world average of 475 gCO2.eq/KWh ( `source `__ ). As you can see, we try to be as accurate as possible in estimating carbon intensity of electricity. Still there is room for improvement and all contributions are welcome. @@ -86,7 +86,7 @@ Tracks Nvidia GPUs energy consumption using ``pynvml`` library (installed with t RAM ~~~~ -CodeCarbon v2 uses a 3 Watts for 8 GB ratio `source `_ . +CodeCarbon v2 uses a 3 Watts for 8 GB ratio `source `__ . But this is not a good measure because it doesn't take into account the number of RAM slots used in the machine, that really drive the power consumption, not the amount of RAM. For example, in servers you could have thousands of GB of RAM but the power consumption would not be proportional to the amount of memory used, but to the number of memory modules used. @@ -143,7 +143,7 @@ CPU - **On Windows or Mac (Intel)** -Tracks Intel processors energy consumption using the ``Intel Power Gadget``. You need to install it yourself from this `source `_ . But has been discontinued. There is a discussion about it on `github issues #457 `_. +Tracks Intel processors energy consumption using the ``Intel Power Gadget``. You need to install it yourself from this `source `__ . But has been discontinued. There is a discussion about it on `github issues #457 `_. - **Apple Silicon Chips (M1, M2)** @@ -179,7 +179,7 @@ All CPUs listed in this directory will be tracked. CPU hardware ------------ -The CPU die is the processing unit itself. It's a piece of semiconductor that has been sculpted/etched/deposited by various manufacturing processes into a net of logic blocks that do stuff that makes computing possible1. The processor package is what you get when you buy a single processor. It contains one or more dies, plastic/ceramic housing for dies and gold-plated contacts that match those on your motherboard. +The CPU die is the processing unit itself. It's a piece of semiconductor that has been sculpted/etched/deposited by various manufacturing processes into a net of logic blocks that do stuff that makes computing possible. The processor package is what you get when you buy a single processor. It contains one or more dies, plastic/ceramic housing for dies and gold-plated contacts that match those on your motherboard. In Linux kernel, energy_uj is a current energy counter in micro joules. It is used to measure CPU core's energy consumption. @@ -191,22 +191,22 @@ For example, on a laptop with Intel(R) Core(TM) i7-7600U, Code Carbon will read RAPL Metrics ------------ -RAPL stand for Running Average Power Limit, it is a feature of processors (CPU) that provide the energy consumption of the processor. +RAPL stands for Running Average Power Limit, it is a feature of processors (CPU) that provide the energy consumption of the processor. See https://blog.chih.me/read-cpu-power-with-RAPL.html for more information. Despite the name Intel RAPL, it support AMD processors since kernel 5.8. -It is some files in /sys/class/powercap/intel-rapl/subsystem/ that give the energy consumption of the CPU, and sometime RAM. -There are folder for each `domain`, and in each folder there are a file `name` with the name of the domain and a `energy_uj` for the amount of energy in micro-joules. +It is some files in /sys/class/powercap/intel-rapl/subsystem/ that give the energy consumption of the CPU, and sometimes RAM. +There are folders for each `domain`, and in each folder there is a file `name` with the name of the domain and an `energy_uj` for the amount of energy in micro-joules. -The drawback of RAPL is that not every CPU use it the same way. We focus on the `package` domain, but some CPU have more domain like `core`, `uncore`, `dram`, `psys`, `gpu`, `psys` and `psys-io`. +The drawback of RAPL is that not every CPU uses it the same way. We focus on the `package` domain, but some CPUs have more domains like `core`, `uncore`, `dram`, `psys`, `gpu`, `psys` and `psys-io`. For example : -- Intel put all the physical cores consumption in `core` and the `package` include `core`. -- For AMD, `core` have very low energy, so we don't know if it is included in the `package` or not. +- Intel puts all the physical cores consumption in `core` and the `package` includes `core`. +- For AMD, `core` has very low energy, so we don't know if it is included in the `package` or not. -Our friend from Scaphandre, a tool to monitor energy consumption, have a good article about RAPL https://hubblo-org.github.io/scaphandre-documentation/explanations/rapl-domains.html and also a discussion with good references: https://github.com/hubblo-org/scaphandre/issues/116#issuecomment-854453231 and point out that this topic is not well documented. +Our friends from Scaphandre, a tool to monitor energy consumption, have a good article about RAPL https://hubblo-org.github.io/scaphandre-documentation/explanations/rapl-domains.html and also a discussion with good references: https://github.com/hubblo-org/scaphandre/issues/116#issuecomment-854453231 and point out that this topic is not well documented. @@ -223,8 +223,8 @@ CodeCarbon : 137 W Power plug measure when loaded (100% CPU): 256 W - 125W in idle = 131 W CorWatt PkgWatt - 133.13 169.82 - 7.54 169.82 +133.13 169.82 +7.54 169.82 CodeCarbon : 330 W package-0-die-0 : 166 W package-0-die-1 : 166 W @@ -237,10 +237,10 @@ CPU metrics priority CodeCarbon will first try to read the energy consumption of the CPU from low level interface like RAPL or ``powermetrics``. If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode: - - It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). - - If the CPU is not found in the data source, a global constant will be applied. - - If ``psutil`` is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. - - CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation. +- It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). +- If the CPU is not found in the data source, a global constant will be applied. +- If ``psutil`` is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. +- CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation. Here is a drawing of the fallback mode: @@ -315,13 +315,15 @@ The equivalent emissions are calculated using this formula: .. math:: \text{Equivalent Emissions} = \frac{\text{Total Emissions (kgCO₂)}}{\text{Emission Factor (kgCO₂/unit)}} -For example: +For example: - **Car Usage**: *1 kWh* of energy consumption is approximately equivalent to: + - *8.33 kilometers driven by a car* (*1 ÷ 0.12*). - *11.9 hours of TV usage* (*1 ÷ 0.084*), if emissions are considered. - **US Citizen Emissions**: + - *1 kWh* of energy consumption can be compared to a fraction of the average weekly emissions of a US citizen: .. math:: diff --git a/docs/_sources/model_examples.rst.txt b/docs/_sources/model_examples.rst.txt index e86480c28..6dd046daa 100644 --- a/docs/_sources/model_examples.rst.txt +++ b/docs/_sources/model_examples.rst.txt @@ -92,7 +92,7 @@ NB : presented on a log scale References ---------- -`Measuring the Carbon intensity of AI in Cloud Instance `_ +`Measuring the Carbon intensity of AI in Cloud Instance `_ Another source comparing models carbon intensity: `Energy and Policy Considerations for Deep Learning in NLP `_ diff --git a/docs/_sources/parameters.rst.txt b/docs/_sources/parameters.rst.txt index 56ceeb949..608df66a5 100644 --- a/docs/_sources/parameters.rst.txt +++ b/docs/_sources/parameters.rst.txt @@ -22,14 +22,14 @@ Input Parameters * - measure_power_secs - Interval (in seconds) to measure hardware power usage, defaults to ``15`` * - tracking_mode - - | ``machine`` measure the power consumptions of the entire machine (defaults) + - | ``machine`` measure the power consumptions of the entire machine (default) | ``process`` try and isolate the tracked processes in isolation * - gpu_ids - | Comma-separated list of GPU ids to track, defaults to ``None`` | These can either be integer indexes of GPUs on the system, or prefixes | to match against GPU identifiers as described `here `_ * - log_level - - | Global codecarbon log level (by order of verbosity): "debug", "info" (defaults), + - | Global codecarbon log level (by order of verbosity): "debug", "info" (default), | "warning", "error", or "critical" * - co2_signal_api_token - | API token for co2signal.com (requires sign-up for free beta) @@ -51,10 +51,10 @@ Input Parameters | on the same machine is allowed, | defaults to ``True`` since v3. Used to be ``False`` in v2. -PUE is a multiplication factor provided by the user, so it is up to the user to get it from his cloud provider. -Old data-centers have a PUE up to 2.2, where new green one could be as low as 1.1. +PUE is a multiplication factor provided by the user, so it is up to the user to get it from their cloud provider. +Old data-centers have a PUE up to 2.2, where new greener ones could be as low as 1.1. -If you, or your provider, use ``CUDA_VISIBLE_DEVICES`` to set the GPU you want to use, CodeCarbon will automaticly set this value to ``gpu_ids``. +If you, or your provider, use ``CUDA_VISIBLE_DEVICES`` to set the GPUs you want to use, CodeCarbon will automaticly populate this value into ``gpu_ids``. If you set ``gpu_ids`` manually, it will override the ``CUDA_VISIBLE_DEVICES`` for CodeCarbon measures. Output parameters @@ -124,9 +124,9 @@ Specific parameters for offline mode * - country_iso_code - | 3-letter ISO Code of the country | where the experiment is being run. - | Available countries are listed in `global_energy_mix.json `_ + | Available countries are listed in `global_energy_mix.json `__ * - region - - | Optional Name of the Province/State/City, where the infrastructure is hosted + - | Optional name of the Province/State/City, where the infrastructure is hosted | Currently, supported only for US States and Canada | for example - California or New York, from the `list `_ * - cloud_provider @@ -159,7 +159,7 @@ Decorator ``track_emissions`` in addition to standard arguments, requires the fo | defaults to ``False`` * - country_iso_code - | 3 letter ISO Code of the country where the experiment is being run. - | Available countries are listed in `global_energy_mix.json `_ + | Available countries are listed in `global_energy_mix.json `__ * - region - | Optional Name of the Province/State/City, where the infrastructure is hosted | Currently, supported only for US States diff --git a/docs/_sources/usage.rst.txt b/docs/_sources/usage.rst.txt index ce2634ae1..dcde88205 100644 --- a/docs/_sources/usage.rst.txt +++ b/docs/_sources/usage.rst.txt @@ -9,7 +9,7 @@ The CO2 tracking tool can be used along with any computing framework. It support Online Mode ----------- When the environment has internet access, the ``EmissionsTracker`` object or the ``track_emissions`` decorator can be used, which has -``offline`` parameter set to ``False`` by default. +the ``offline`` parameter set to ``False`` by default. Command line ~~~~~~~~~~~~ diff --git a/docs/advanced_installation.html b/docs/advanced_installation.html index 88434e68a..5155936c4 100644 --- a/docs/advanced_installation.html +++ b/docs/advanced_installation.html @@ -235,7 +235,7 @@

Directory Structure

  1. Set the the target to install in hosts:

    -
    yourservername.yourdomain.com   hostname=yourservername ansible_user=root ansible_ssh_private_key_file=~/.ssh/id_ed25519
+
    yourservername.yourdomain.com   hostname=yourservername ansible_user=root ansible_ssh_private_key_file=~/.ssh/id_ed25519
    2. diff --git a/docs/edit/advanced_installation.rst b/docs/edit/advanced_installation.rst index 130d4060c..3c89dcf26 100644 --- a/docs/edit/advanced_installation.rst +++ b/docs/edit/advanced_installation.rst @@ -122,7 +122,7 @@ This section describes how to deploy CodeCarbon as a system service using Ansibl It automate the manual installation done in the previous chapter. What the Playbook Does --------------------- +---------------------- The Ansible playbook automates the following tasks: * Creates a dedicated system user and group for CodeCarbon @@ -134,14 +134,14 @@ The Ansible playbook automates the following tasks: * Starts and enables the service Prerequisites ------------- +------------- * Ansible installed on your machine * Debian-based target system(s) * SSH access to target system(s) * CodeCarbon API credentials from the dashboard Directory Structure ------------------ +------------------- .. code-block:: text codecarbon/deploy/ansible/codecarbon_cli_as_a_service/ @@ -158,11 +158,11 @@ Directory Structure └── main.yml Quick Start ----------- +----------- 1. Set the the target to install in ``hosts``: - .. code-block:: txt + .. code-block:: text yourservername.yourdomain.com hostname=yourservername ansible_user=root ansible_ssh_private_key_file=~/.ssh/id_ed25519 diff --git a/docs/edit/comet.rst b/docs/edit/comet.rst index 7219e9bee..b1ac48f4a 100644 --- a/docs/edit/comet.rst +++ b/docs/edit/comet.rst @@ -4,7 +4,7 @@ Comet Integration =========================== -CodeCarbon can be automatically integrated with `Comet `_ for experiment tracking and visualization. Comet provides data scientists with powerful tools to track, compare, explain, and reproduce their experiments. Now, with CodeCarbon you can easily track the carbon footprint of your jobs along with your training metrics, hyperparameters, dataset samples, artifacts, and more. +CodeCarbon can be automatically integrated with `Comet `__ for experiment tracking and visualization. Comet provides data scientists with powerful tools to track, compare, explain, and reproduce their experiments. Now, with CodeCarbon you can easily track the carbon footprint of your jobs along with your training metrics, hyperparameters, dataset samples, artifacts, and more. .. image:: ./images/comet-workspace.png :align: center @@ -19,7 +19,7 @@ To get started with the Comet-CodeCarbon integration, make sure you have comet-m pip install comet_ml>=3.2.2 -Go to `Comet's website `_ and create a free account. From your account settings page, copy your personal API key. +Go to `Comet's website `__ and create a free account. From your account settings page, copy your personal API key. In the `mnist-comet.py `_ example file, replace the placeholder code with your API key: diff --git a/docs/edit/faq.rst b/docs/edit/faq.rst index 220559248..b6fe5977e 100644 --- a/docs/edit/faq.rst +++ b/docs/edit/faq.rst @@ -22,9 +22,9 @@ Frequently Asked Questions - When available we use data from `ourworld in data `_ - - if not available we use the electricity mix of the country find on `globalpetrolprices.com `_ that we multiply by the carbon intensity of the source of electricity (`that you can find here `_) + - If not available we use the electricity mix of the country find on `globalpetrolprices.com `_ that we multiply by the carbon intensity of the source of electricity (`that you can find here `_) - - if we have neither we default to a world average of 475 gCO2.eq/KWh from `IEA `_. + - If we have neither we default to a world average of 475 gCO2.eq/KWh from `IEA `_. * **How do I offset my emissions?** @@ -32,6 +32,6 @@ Frequently Asked Questions * **How can I help?** - If you find a functionality missing in the CodeCarbon repo, please `open an issue `_ so that you (and others!) can help add it. We did our best to cover all use cases and options, but we count on the open source community to help make the package an even greater success. + If you find any functionality missing in the CodeCarbon repo, please `open an issue `_ so that you (and others!) can help add it. We did our best to cover all use cases and options, but we count on the open source community to help make the package an even greater success. diff --git a/docs/edit/installation.rst b/docs/edit/installation.rst index 0e5cf619f..a46efccfd 100755 --- a/docs/edit/installation.rst +++ b/docs/edit/installation.rst @@ -15,7 +15,7 @@ For installing conda, follow the instructions on the From PyPi repository -------------------- -The package is hosted on the pip repository `here `_. +The package is hosted on the pip repository `here `__. To install the package, run the following command in your terminal. @@ -26,7 +26,7 @@ To install the package, run the following command in your terminal. From conda repository --------------------- -The package is hosted on the conda repository `here `_. +The package is hosted on the conda repository `here `__. To install the package, run the following command in your terminal. diff --git a/docs/edit/methodology.rst b/docs/edit/methodology.rst index f235923f1..56142cb91 100644 --- a/docs/edit/methodology.rst +++ b/docs/edit/methodology.rst @@ -24,7 +24,7 @@ energy sources that are used to generate electricity, including fossil fuels and :height: 300px :width: 350px -When available, CodeCarbon uses global carbon intensity of electricity per cloud provider ( `here `_ ) or per country ( `here `_ ). +When available, CodeCarbon uses global carbon intensity of electricity per cloud provider ( `here `__) or per country ( `here `__ ). If we don't have the global carbon intensity or electricity of a country, but we have its electricity mix, we used to compute the carbon intensity of electricity using this table: @@ -63,9 +63,9 @@ Then, for example, if the Energy Mix of the Grid Electricity is 25% Coal, 35% Pe Net Carbon Intensity = 0.25 * 995 + 0.35 * 816 + 0.26 * 743 + 0.14 * 29 = 731.59 kgCO₂/kWh -But it doesn't happen anymore because Our World in Data now provides the global carbon intensity of electricity per country ( `source `_ ). Some countries are missing data for last year, so we use the previous year data available. +But it doesn't happen anymore because Our World in Data now provides the global carbon intensity of electricity per country ( `source `__ ). Some countries are missing data for last year, so we use the previous year data available. -If ever we have neither the global carbon intensity of a country nor it's electricity mix, we apply a world average of 475 gCO2.eq/KWh ( `source `_ ). +If ever we have neither the global carbon intensity of a country nor it's electricity mix, we apply a world average of 475 gCO2.eq/KWh ( `source `__ ). As you can see, we try to be as accurate as possible in estimating carbon intensity of electricity. Still there is room for improvement and all contributions are welcome. @@ -86,7 +86,7 @@ Tracks Nvidia GPUs energy consumption using ``pynvml`` library (installed with t RAM ~~~~ -CodeCarbon v2 uses a 3 Watts for 8 GB ratio `source `_ . +CodeCarbon v2 uses a 3 Watts for 8 GB ratio `source `__ . But this is not a good measure because it doesn't take into account the number of RAM slots used in the machine, that really drive the power consumption, not the amount of RAM. For example, in servers you could have thousands of GB of RAM but the power consumption would not be proportional to the amount of memory used, but to the number of memory modules used. @@ -143,7 +143,7 @@ CPU - **On Windows or Mac (Intel)** -Tracks Intel processors energy consumption using the ``Intel Power Gadget``. You need to install it yourself from this `source `_ . But has been discontinued. There is a discussion about it on `github issues #457 `_. +Tracks Intel processors energy consumption using the ``Intel Power Gadget``. You need to install it yourself from this `source `__ . But has been discontinued. There is a discussion about it on `github issues #457 `_. - **Apple Silicon Chips (M1, M2)** @@ -179,7 +179,7 @@ All CPUs listed in this directory will be tracked. CPU hardware ------------ -The CPU die is the processing unit itself. It's a piece of semiconductor that has been sculpted/etched/deposited by various manufacturing processes into a net of logic blocks that do stuff that makes computing possible1. The processor package is what you get when you buy a single processor. It contains one or more dies, plastic/ceramic housing for dies and gold-plated contacts that match those on your motherboard. +The CPU die is the processing unit itself. It's a piece of semiconductor that has been sculpted/etched/deposited by various manufacturing processes into a net of logic blocks that do stuff that makes computing possible. The processor package is what you get when you buy a single processor. It contains one or more dies, plastic/ceramic housing for dies and gold-plated contacts that match those on your motherboard. In Linux kernel, energy_uj is a current energy counter in micro joules. It is used to measure CPU core's energy consumption. @@ -191,22 +191,22 @@ For example, on a laptop with Intel(R) Core(TM) i7-7600U, Code Carbon will read RAPL Metrics ------------ -RAPL stand for Running Average Power Limit, it is a feature of processors (CPU) that provide the energy consumption of the processor. +RAPL stands for Running Average Power Limit, it is a feature of processors (CPU) that provide the energy consumption of the processor. See https://blog.chih.me/read-cpu-power-with-RAPL.html for more information. Despite the name Intel RAPL, it support AMD processors since kernel 5.8. -It is some files in /sys/class/powercap/intel-rapl/subsystem/ that give the energy consumption of the CPU, and sometime RAM. -There are folder for each `domain`, and in each folder there are a file `name` with the name of the domain and a `energy_uj` for the amount of energy in micro-joules. +It is some files in /sys/class/powercap/intel-rapl/subsystem/ that give the energy consumption of the CPU, and sometimes RAM. +There are folders for each `domain`, and in each folder there is a file `name` with the name of the domain and an `energy_uj` for the amount of energy in micro-joules. -The drawback of RAPL is that not every CPU use it the same way. We focus on the `package` domain, but some CPU have more domain like `core`, `uncore`, `dram`, `psys`, `gpu`, `psys` and `psys-io`. +The drawback of RAPL is that not every CPU uses it the same way. We focus on the `package` domain, but some CPUs have more domains like `core`, `uncore`, `dram`, `psys`, `gpu`, `psys` and `psys-io`. For example : -- Intel put all the physical cores consumption in `core` and the `package` include `core`. -- For AMD, `core` have very low energy, so we don't know if it is included in the `package` or not. +- Intel puts all the physical cores consumption in `core` and the `package` includes `core`. +- For AMD, `core` has very low energy, so we don't know if it is included in the `package` or not. -Our friend from Scaphandre, a tool to monitor energy consumption, have a good article about RAPL https://hubblo-org.github.io/scaphandre-documentation/explanations/rapl-domains.html and also a discussion with good references: https://github.com/hubblo-org/scaphandre/issues/116#issuecomment-854453231 and point out that this topic is not well documented. +Our friends from Scaphandre, a tool to monitor energy consumption, have a good article about RAPL https://hubblo-org.github.io/scaphandre-documentation/explanations/rapl-domains.html and also a discussion with good references: https://github.com/hubblo-org/scaphandre/issues/116#issuecomment-854453231 and point out that this topic is not well documented. @@ -223,8 +223,8 @@ CodeCarbon : 137 W Power plug measure when loaded (100% CPU): 256 W - 125W in idle = 131 W CorWatt PkgWatt - 133.13 169.82 - 7.54 169.82 +133.13 169.82 +7.54 169.82 CodeCarbon : 330 W package-0-die-0 : 166 W package-0-die-1 : 166 W @@ -237,10 +237,10 @@ CPU metrics priority CodeCarbon will first try to read the energy consumption of the CPU from low level interface like RAPL or ``powermetrics``. If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode: - - It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). - - If the CPU is not found in the data source, a global constant will be applied. - - If ``psutil`` is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. - - CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation. +- It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). +- If the CPU is not found in the data source, a global constant will be applied. +- If ``psutil`` is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. +- CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation. Here is a drawing of the fallback mode: @@ -315,13 +315,15 @@ The equivalent emissions are calculated using this formula: .. math:: \text{Equivalent Emissions} = \frac{\text{Total Emissions (kgCO₂)}}{\text{Emission Factor (kgCO₂/unit)}} -For example: +For example: - **Car Usage**: *1 kWh* of energy consumption is approximately equivalent to: + - *8.33 kilometers driven by a car* (*1 ÷ 0.12*). - *11.9 hours of TV usage* (*1 ÷ 0.084*), if emissions are considered. - **US Citizen Emissions**: + - *1 kWh* of energy consumption can be compared to a fraction of the average weekly emissions of a US citizen: .. math:: diff --git a/docs/edit/model_examples.rst b/docs/edit/model_examples.rst index e86480c28..6dd046daa 100644 --- a/docs/edit/model_examples.rst +++ b/docs/edit/model_examples.rst @@ -92,7 +92,7 @@ NB : presented on a log scale References ---------- -`Measuring the Carbon intensity of AI in Cloud Instance `_ +`Measuring the Carbon intensity of AI in Cloud Instance `_ Another source comparing models carbon intensity: `Energy and Policy Considerations for Deep Learning in NLP `_ diff --git a/docs/edit/parameters.rst b/docs/edit/parameters.rst index 56ceeb949..608df66a5 100644 --- a/docs/edit/parameters.rst +++ b/docs/edit/parameters.rst @@ -22,14 +22,14 @@ Input Parameters * - measure_power_secs - Interval (in seconds) to measure hardware power usage, defaults to ``15`` * - tracking_mode - - | ``machine`` measure the power consumptions of the entire machine (defaults) + - | ``machine`` measure the power consumptions of the entire machine (default) | ``process`` try and isolate the tracked processes in isolation * - gpu_ids - | Comma-separated list of GPU ids to track, defaults to ``None`` | These can either be integer indexes of GPUs on the system, or prefixes | to match against GPU identifiers as described `here `_ * - log_level - - | Global codecarbon log level (by order of verbosity): "debug", "info" (defaults), + - | Global codecarbon log level (by order of verbosity): "debug", "info" (default), | "warning", "error", or "critical" * - co2_signal_api_token - | API token for co2signal.com (requires sign-up for free beta) @@ -51,10 +51,10 @@ Input Parameters | on the same machine is allowed, | defaults to ``True`` since v3. Used to be ``False`` in v2. -PUE is a multiplication factor provided by the user, so it is up to the user to get it from his cloud provider. -Old data-centers have a PUE up to 2.2, where new green one could be as low as 1.1. +PUE is a multiplication factor provided by the user, so it is up to the user to get it from their cloud provider. +Old data-centers have a PUE up to 2.2, where new greener ones could be as low as 1.1. -If you, or your provider, use ``CUDA_VISIBLE_DEVICES`` to set the GPU you want to use, CodeCarbon will automaticly set this value to ``gpu_ids``. +If you, or your provider, use ``CUDA_VISIBLE_DEVICES`` to set the GPUs you want to use, CodeCarbon will automaticly populate this value into ``gpu_ids``. If you set ``gpu_ids`` manually, it will override the ``CUDA_VISIBLE_DEVICES`` for CodeCarbon measures. Output parameters @@ -124,9 +124,9 @@ Specific parameters for offline mode * - country_iso_code - | 3-letter ISO Code of the country | where the experiment is being run. - | Available countries are listed in `global_energy_mix.json `_ + | Available countries are listed in `global_energy_mix.json `__ * - region - - | Optional Name of the Province/State/City, where the infrastructure is hosted + - | Optional name of the Province/State/City, where the infrastructure is hosted | Currently, supported only for US States and Canada | for example - California or New York, from the `list `_ * - cloud_provider @@ -159,7 +159,7 @@ Decorator ``track_emissions`` in addition to standard arguments, requires the fo | defaults to ``False`` * - country_iso_code - | 3 letter ISO Code of the country where the experiment is being run. - | Available countries are listed in `global_energy_mix.json `_ + | Available countries are listed in `global_energy_mix.json `__ * - region - | Optional Name of the Province/State/City, where the infrastructure is hosted | Currently, supported only for US States diff --git a/docs/edit/usage.rst b/docs/edit/usage.rst index ce2634ae1..dcde88205 100644 --- a/docs/edit/usage.rst +++ b/docs/edit/usage.rst @@ -9,7 +9,7 @@ The CO2 tracking tool can be used along with any computing framework. It support Online Mode ----------- When the environment has internet access, the ``EmissionsTracker`` object or the ``track_emissions`` decorator can be used, which has -``offline`` parameter set to ``False`` by default. +the ``offline`` parameter set to ``False`` by default. Command line ~~~~~~~~~~~~ diff --git a/docs/faq.html b/docs/faq.html index 96d3c41e1..2984adba5 100644 --- a/docs/faq.html +++ b/docs/faq.html @@ -111,8 +111,8 @@

    For private infra:

    • When available we use data from ourworld in data

      • -

    • if not available we use the electricity mix of the country find on globalpetrolprices.com that we multiply by the carbon intensity of the source of electricity (that you can find here)

      • -

    • if we have neither we default to a world average of 475 gCO2.eq/KWh from IEA.

      • +

    • If not available we use the electricity mix of the country find on globalpetrolprices.com that we multiply by the carbon intensity of the source of electricity (that you can find here)

      • +

    • If we have neither we default to a world average of 475 gCO2.eq/KWh from IEA.

    @@ -124,7 +124,7 @@
  2. -
    How can I help?

    If you find a functionality missing in the CodeCarbon repo, please open an issue so that you (and others!) can help add it. We did our best to cover all use cases and options, but we count on the open source community to help make the package an even greater success.

    +
    How can I help?

    If you find any functionality missing in the CodeCarbon repo, please open an issue so that you (and others!) can help add it. We did our best to cover all use cases and options, but we count on the open source community to help make the package an even greater success.

    3. diff --git a/docs/methodology.html b/docs/methodology.html index c9ab571bc..b8f73069a 100644 --- a/docs/methodology.html +++ b/docs/methodology.html @@ -131,10 +131,10 @@

    Carbon IntensityGrid Energy Mix -

    When available, CodeCarbon uses global carbon intensity of electricity per cloud provider ( here ) or per country ( here ).

    +

    When available, CodeCarbon uses global carbon intensity of electricity per cloud provider ( here) or per country ( here ).

    If we don’t have the global carbon intensity or electricity of a country, but we have its electricity mix, we used to compute the carbon intensity of electricity using this table:

    - - +
    Carbon Intensity Across Energy Sources
    +@@ -270,7 +270,7 @@

    CPU

    CPU hardware

    -

    The CPU die is the processing unit itself. It’s a piece of semiconductor that has been sculpted/etched/deposited by various manufacturing processes into a net of logic blocks that do stuff that makes computing possible1. The processor package is what you get when you buy a single processor. It contains one or more dies, plastic/ceramic housing for dies and gold-plated contacts that match those on your motherboard.

    +

    The CPU die is the processing unit itself. It’s a piece of semiconductor that has been sculpted/etched/deposited by various manufacturing processes into a net of logic blocks that do stuff that makes computing possible. The processor package is what you get when you buy a single processor. It contains one or more dies, plastic/ceramic housing for dies and gold-plated contacts that match those on your motherboard.

    In Linux kernel, energy_uj is a current energy counter in micro joules. It is used to measure CPU core’s energy consumption.

    Micro joules is then converted in kWh, with formulas kWh=energy * 10 ** (-6) * 2.77778e-7

    For example, on a laptop with Intel(R) Core(TM) i7-7600U, Code Carbon will read two files : @@ -278,16 +278,16 @@

    CPU hardware

    RAPL Metrics

    -

    RAPL stand for Running Average Power Limit, it is a feature of processors (CPU) that provide the energy consumption of the processor.

    +

    RAPL stands for Running Average Power Limit, it is a feature of processors (CPU) that provide the energy consumption of the processor.

    See https://blog.chih.me/read-cpu-power-with-RAPL.html for more information.

    Despite the name Intel RAPL, it support AMD processors since kernel 5.8.

    -

    It is some files in /sys/class/powercap/intel-rapl/subsystem/ that give the energy consumption of the CPU, and sometime RAM. -There are folder for each domain, and in each folder there are a file name with the name of the domain and a energy_uj for the amount of energy in micro-joules.

    -

    The drawback of RAPL is that not every CPU use it the same way. We focus on the package domain, but some CPU have more domain like core, uncore, dram, psys, gpu, psys and psys-io.

    +

    It is some files in /sys/class/powercap/intel-rapl/subsystem/ that give the energy consumption of the CPU, and sometimes RAM. +There are folders for each domain, and in each folder there is a file name with the name of the domain and an energy_uj for the amount of energy in micro-joules.

    +

    The drawback of RAPL is that not every CPU uses it the same way. We focus on the package domain, but some CPUs have more domains like core, uncore, dram, psys, gpu, psys and psys-io.

    For example : -- Intel put all the physical cores consumption in core and the package include core. -- For AMD, core have very low energy, so we don’t know if it is included in the package or not.

    -

    Our friend from Scaphandre, a tool to monitor energy consumption, have a good article about RAPL https://hubblo-org.github.io/scaphandre-documentation/explanations/rapl-domains.html and also a discussion with good references: https://github.com/hubblo-org/scaphandre/issues/116#issuecomment-854453231 and point out that this topic is not well documented.

    +- Intel puts all the physical cores consumption in core and the package includes core. +- For AMD, core has very low energy, so we don’t know if it is included in the package or not.

    +

    Our friends from Scaphandre, a tool to monitor energy consumption, have a good article about RAPL https://hubblo-org.github.io/scaphandre-documentation/explanations/rapl-domains.html and also a discussion with good references: https://github.com/hubblo-org/scaphandre/issues/116#issuecomment-854453231 and point out that this topic is not well documented.

    https://user-images.githubusercontent.com/894892/120764898-ecf07280-c518-11eb-9155-92780cabcf52.png Source :“RAPL in Action: Experiences in Using RAPL for Power Measurements,” (K. N. Khan, M. Hirki, T. Niemi, J. K. Nurminen, and Z. Ou, ACM Trans. Model. Perform. Eval. Comput. Syst., vol. 3, no. 2, pp. 1–26, Apr. 2018, doi: 10.1145/3177754.)

    Metric comparison

    @@ -297,12 +297,10 @@

    RAPL Metrics

    CPU metrics priority

    CodeCarbon will first try to read the energy consumption of the CPU from low level interface like RAPL or powermetrics. -If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode:

    -
    -
      -

    • It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs).

      • -

    • If the CPU is not found in the data source, a global constant will be applied.

      • -

    • If psutil is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load.

      • -

    • CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation.

      • -
    -
    +If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode: +- It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). +- If the CPU is not found in the data source, a global constant will be applied. +- If psutil is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. +- CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation.

    Here is a drawing of the fallback mode:

    CPU Fallback

    The code doing this is available in codecarbon/core/resource_tracker.py.

    @@ -374,13 +368,20 @@

    Calculation Formula \[\text{Equivalent Emissions} = \frac{\text{Total Emissions (kgCO₂)}}{\text{Emission Factor (kgCO₂/unit)}}\] -

    For example:

    +

    For example: +- Car Usage: 1 kWh of energy consumption is approximately equivalent to:

    +
    +
      +

    • 8.33 kilometers driven by a car (1 ÷ 0.12).

      • +

    • 11.9 hours of TV usage (1 ÷ 0.084), if emissions are considered.

      • +
    +
      -

    • Car Usage: 1 kWh of energy consumption is approximately equivalent to: -- 8.33 kilometers driven by a car (1 ÷ 0.12). -- 11.9 hours of TV usage (1 ÷ 0.084), if emissions are considered.

      • -

    • US Citizen Emissions: -- 1 kWh of energy consumption can be compared to a fraction of the average weekly emissions of a US citizen:

      • +

    • US Citizen Emissions:

      +
        +

      • 1 kWh of energy consumption can be compared to a fraction of the average weekly emissions of a US citizen:

        • +
      +
    \[\text{US Citizen Equivalent} = \frac{\text{Total Emissions (tons)}}{0.256}\]
    diff --git a/docs/model_examples.html b/docs/model_examples.html index ee2806e98..3e9ef4d42 100644 --- a/docs/model_examples.html +++ b/docs/model_examples.html @@ -191,7 +191,7 @@

    Comparisons

    References

    -

    Measuring the Carbon intensity of AI in Cloud Instance

    +

    Measuring the Carbon intensity of AI in Cloud Instance

    Another source comparing models carbon intensity: Energy and Policy Considerations for Deep Learning in NLP

    diff --git a/docs/parameters.html b/docs/parameters.html index 5a349fccb..966d4ee32 100644 --- a/docs/parameters.html +++ b/docs/parameters.html @@ -102,8 +102,8 @@

    A set of parameters are supported by API to help users provide additional details per project.

    Input Parameters

    -

    Carbon Intensity Across Energy Sources
    - +
    Input Parameters
    +@@ -125,7 +125,7 @@

    Input Parameters

    @@ -140,7 +140,7 @@

    Input Parameters

    @@ -186,15 +186,15 @@

    Input ParametersCUDA_VISIBLE_DEVICES to set the GPU you want to use, CodeCarbon will automaticly set this value to gpu_ids. +

    PUE is a multiplication factor provided by the user, so it is up to the user to get it from their cloud provider. +Old data-centers have a PUE up to 2.2, where new greener ones could be as low as 1.1.

    +

    If you, or your provider, use CUDA_VISIBLE_DEVICES to set the GPUs you want to use, CodeCarbon will automaticly populate this value into gpu_ids. If you set gpu_ids manually, it will override the CUDA_VISIBLE_DEVICES for CodeCarbon measures.

    Output parameters

    -

    Input Parameters

    tracking_mode
    -
    machine measure the power consumptions of the entire machine (defaults)
    +
    machine measure the power consumptions of the entire machine (default)
    process try and isolate the tracked processes in isolation

    log_level
    -
    Global codecarbon log level (by order of verbosity): “debug”, “info” (defaults),
    +
    Global codecarbon log level (by order of verbosity): “debug”, “info” (default),
    “warning”, “error”, or “critical”
    - +
    Output Parameters
    +@@ -305,8 +305,8 @@

    Output parameters

    Specific parameters for offline mode

    -

    Output Parameters
    - +
    Input Parameters to OfflineEmissionsTracker
    +@@ -327,7 +327,7 @@

    Specific parameters for offline mode

    Input Parameters to OfflineEmissionsTracker

    region
    -
    Optional Name of the Province/State/City, where the infrastructure is hosted
    +
    Optional name of the Province/State/City, where the infrastructure is hosted
    Currently, supported only for US States and Canada
    for example - California or New York, from the list
    @@ -360,8 +360,8 @@

    Specific parameters for offline mode

    @track_emissions

    Decorator track_emissions in addition to standard arguments, requires the following parameters:

    - - +
    Input Parameters to @track_emissions
    +diff --git a/docs/searchindex.js b/docs/searchindex.js index 70aa19011..e3478ddd9 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1,5 @@ -Search.setIndex({"alltitles":{"@track_emissions":[[23,"track-emissions"]],"Access internet through proxy server":[[26,"access-internet-through-proxy-server"]],"Advanced Installation":[[12,null]],"Authentication":[[25,"authentication"]],"CPU":[[19,"cpu"]],"CPU hardware":[[19,"cpu-hardware"]],"CPU metrics priority":[[19,"cpu-metrics-priority"]],"CSV":[[22,"csv"]],"Calculation Formula":[[19,"calculation-formula"]],"Car Usage":[[19,"car-usage"]],"Carbon Intensity":[[19,"carbon-intensity"]],"Carbon Intensity Across Energy Sources":[[19,"id6"]],"Cloud Regions":[[27,"cloud-regions"]],"CodeCarbon":[[17,null]],"CodeCarbon API":[[13,null],[13,"id1"],[22,"codecarbon-api"]],"Collecting emissions to a logger":[[25,null]],"Comet Integration":[[14,null]],"Command line":[[26,"command-line"]],"Comparisons":[[20,"comparisons"]],"Configuration":[[26,"configuration"]],"Configuration priority":[[26,"configuration-priority"]],"Context manager":[[26,"context-manager"],[26,"id2"]],"Create a logger":[[25,"create-a-logger"]],"Create an EmissionTracker":[[25,"create-an-emissiontracker"]],"Data Fields Logged for Each Experiment":[[22,"id4"]],"Decorator":[[26,"decorator"],[26,"id3"]],"Dependencies":[[18,"dependencies"]],"Deploy CodeCarbon CLI as a Service using Ansible":[[12,"deploy-codecarbon-cli-as-a-service-using-ansible"]],"Directory Structure":[[12,"directory-structure"]],"Electricity consumption of AI cloud instance":[[20,"id1"]],"Electricity production carbon intensity per country":[[27,"electricity-production-carbon-intensity-per-country"]],"Estimation of Equivalent Usage Emissions":[[19,"estimation-of-equivalent-usage-emissions"]],"Example":[[25,"example"]],"Examples":[[15,null]],"Explicit Object":[[26,"explicit-object"],[26,"id1"]],"Frequently Asked Questions":[[16,null]],"From PyPi repository":[[18,"from-pypi-repository"]],"From conda repository":[[18,"from-conda-repository"]],"GPU":[[19,"gpu"]],"Getting Started":[[17,null]],"Google Cloud Logging":[[25,"google-cloud-logging"]],"HTTP Output":[[22,"http-output"]],"How CodeCarbon Works":[[19,"how-codecarbon-works"]],"How to test in local":[[22,"how-to-test-in-local"]],"How to use it":[[22,"how-to-use-it"]],"Impact of time of year and region":[[20,"impact-of-time-of-year-and-region"]],"Indices and tables":[[17,"indices-and-tables"]],"Input Parameters":[[23,"input-parameters"],[23,"id7"]],"Input Parameters to @track_emissions":[[23,"id10"]],"Input Parameters to OfflineEmissionsTracker":[[23,"id9"]],"Install CodeCarbon as a Linux service":[[12,"install-codecarbon-as-a-linux-service"]],"Installing CodeCarbon":[[18,null]],"Introduction":[[17,null]],"Logfire":[[22,"logfire"]],"Logger Output":[[22,"logger-output"]],"Logging":[[17,null]],"Methodology":[[19,null]],"Model 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+>>>>>>> 356fdcae (Fix some typos and sphinx warnings.) diff --git a/docs/usage.html b/docs/usage.html index 1dff652ef..d1088ea77 100644 --- a/docs/usage.html +++ b/docs/usage.html @@ -117,7 +117,7 @@

    Online Mode

    When the environment has internet access, the EmissionsTracker object or the track_emissions decorator can be used, which has -offline parameter set to False by default.

    +the offline parameter set to False by default.

    Command line

    Create a minimal configuration file (just follow the prompts) :

    From a75b8db99da2010523f6583fa69e4a85a48a8925 Mon Sep 17 00:00:00 2001 From: cianc Date: Wed, 17 Sep 2025 10:31:32 +0100 Subject: [PATCH 2/2] Add missing blank lines to fix lists --- docs/_sources/methodology.rst.txt | 2 ++ docs/edit/methodology.rst | 2 ++ docs/methodology.html | 23 ++++++++++++----------- 3 files changed, 16 insertions(+), 11 deletions(-) diff --git a/docs/_sources/methodology.rst.txt b/docs/_sources/methodology.rst.txt index 56142cb91..0c2ee6d4e 100644 --- a/docs/_sources/methodology.rst.txt +++ b/docs/_sources/methodology.rst.txt @@ -237,6 +237,7 @@ CPU metrics priority CodeCarbon will first try to read the energy consumption of the CPU from low level interface like RAPL or ``powermetrics``. If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode: + - It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). - If the CPU is not found in the data source, a global constant will be applied. - If ``psutil`` is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. @@ -317,6 +318,7 @@ The equivalent emissions are calculated using this formula: \text{Equivalent Emissions} = \frac{\text{Total Emissions (kgCO₂)}}{\text{Emission Factor (kgCO₂/unit)}} For example: + - **Car Usage**: *1 kWh* of energy consumption is approximately equivalent to: - *8.33 kilometers driven by a car* (*1 ÷ 0.12*). diff --git a/docs/edit/methodology.rst b/docs/edit/methodology.rst index 56142cb91..0c2ee6d4e 100644 --- a/docs/edit/methodology.rst +++ b/docs/edit/methodology.rst @@ -237,6 +237,7 @@ CPU metrics priority CodeCarbon will first try to read the energy consumption of the CPU from low level interface like RAPL or ``powermetrics``. If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode: + - It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). - If the CPU is not found in the data source, a global constant will be applied. - If ``psutil`` is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. @@ -317,6 +318,7 @@ The equivalent emissions are calculated using this formula: \text{Equivalent Emissions} = \frac{\text{Total Emissions (kgCO₂)}}{\text{Emission Factor (kgCO₂/unit)}} For example: + - **Car Usage**: *1 kWh* of energy consumption is approximately equivalent to: - *8.33 kilometers driven by a car* (*1 ÷ 0.12*). diff --git a/docs/methodology.html b/docs/methodology.html index b8f73069a..a51c4bcc4 100644 --- a/docs/methodology.html +++ b/docs/methodology.html @@ -308,11 +308,13 @@

    RAPL Metrics

    CPU metrics priority

    CodeCarbon will first try to read the energy consumption of the CPU from low level interface like RAPL or powermetrics. -If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode: -- It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs). -- If the CPU is not found in the data source, a global constant will be applied. -- If psutil is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load. -- CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation.

    +If none of the tracking tools are available, CodeCarbon will be switched to a fallback mode:

    +
      +

    • It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs).

      • +

    • If the CPU is not found in the data source, a global constant will be applied.

      • +

    • If psutil is available, CodeCarbon will try to estimate the energy consumption from the TDP and the CPU load.

      • +

    • CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation.

      • +

    Here is a drawing of the fallback mode:

    CPU Fallback

    The code doing this is available in codecarbon/core/resource_tracker.py.

    @@ -368,15 +370,14 @@

    Calculation Formula \[\text{Equivalent Emissions} = \frac{\text{Total Emissions (kgCO₂)}}{\text{Emission Factor (kgCO₂/unit)}}\] -

    For example: -- Car Usage: 1 kWh of energy consumption is approximately equivalent to:

    -
    -
      +

      For example:

      +
        +

      • Car Usage: 1 kWh of energy consumption is approximately equivalent to:

        +

        • 8.33 kilometers driven by a car (1 ÷ 0.12).

        • 11.9 hours of TV usage (1 ÷ 0.084), if emissions are considered.

        -
    -
      +

    • US Citizen Emissions:

      • 1 kWh of energy consumption can be compared to a fraction of the average weekly emissions of a US citizen:

    Input Parameters to @track_emissions