rename observed types

Author: iProzd

deepmd/entrypoints/show.py

@@ -73,31 +73,33 @@ def show(
         for k in sorted(size_dict):
             log.info(f"Parameters in {k}: {size_dict[k]:,}")
 
-    if "type-coverage" in ATTRIBUTES:
+    if "observed-type" in ATTRIBUTES:
         if model_is_multi_task:
-            log.info("The type coverage for each branch: ")
-            total_type_coverage_list = []
+            log.info("The observed types for each branch: ")
+            total_observed_types_list = []
             model_branches = list(model_params["model_dict"].keys())
             for branch in model_branches:
                 tmp_model = DeepEval(INPUT, head=branch, no_jit=True)
-                type_coverage = tmp_model.get_type_coverage()
+                observed_types = tmp_model.get_observed_types()
                 log.info(
-                    f"{branch}: Number of covered types: {type_coverage['type_num']} "
+                    f"{branch}: Number of observed types: {observed_types['type_num']} "
                 )
-                log.info(f"{branch}: Covered types: {type_coverage['covered_type']} ")
-                total_type_coverage_list += [
+                log.info(
+                    f"{branch}: Observed types: {observed_types['observed_type']} "
+                )
+                total_observed_types_list += [
                     tt
-                    for tt in type_coverage["covered_type"]
-                    if tt not in total_type_coverage_list
+                    for tt in observed_types["observed_type"]
+                    if tt not in total_observed_types_list
                 ]
             log.info(
-                f"TOTAL number of covered types in the model: {len(total_type_coverage_list)} "
+                f"TOTAL number of observed types in the model: {len(total_observed_types_list)} "
             )
             log.info(
-                f"TOTAL covered types in the model: {sort_element_type(total_type_coverage_list)} "
+                f"TOTAL observed types in the model: {sort_element_type(total_observed_types_list)} "
             )
         else:
-            log.info("The type coverage for this model: ")
-            type_coverage = model.get_type_coverage()
-            log.info(f"Number of covered types: {type_coverage['type_num']} ")
-            log.info(f"Covered types: {type_coverage['covered_type']} ")
+            log.info("The observed types for this model: ")
+            observed_types = model.get_observed_types()
+            log.info(f"Number of observed types: {observed_types['type_num']} ")
+            log.info(f"Observed types: {observed_types['observed_type']} ")

deepmd/infer/deep_eval.py

@@ -295,8 +295,8 @@ def get_model_size(self) -> dict:
         """Get model parameter count."""
         raise NotImplementedError("Not implemented in this backend.")
 
-    def get_type_coverage(self) -> dict:
-        """Get model type (element) coverage."""
+    def get_observed_types(self) -> dict:
+        """Get observed types (elements) during model training."""
         raise NotImplementedError("Not implemented in this backend.")
 
 
@@ -573,6 +573,6 @@ def get_model_size(self) -> dict:
         """Get model parameter count."""
         return self.deep_eval.get_model_size()
 
-    def get_type_coverage(self) -> dict:
-        """Get model type (element) coverage."""
-        return self.deep_eval.get_type_coverage()
+    def get_observed_types(self) -> dict:
+        """Get observed types (elements) during model training."""
+        return self.deep_eval.get_observed_types()

deepmd/main.py

@@ -857,7 +857,7 @@ def main_parser() -> argparse.ArgumentParser:
             "descriptor",
             "fitting-net",
             "size",
-            "type-coverage",
+            "observed-type",
         ],
         nargs="+",
     )

deepmd/pt/infer/deep_eval.py

@@ -652,15 +652,15 @@ def get_model_size(self) -> dict:
             "total": sum_param_des + sum_param_fit,
         }
 
-    def get_type_coverage(self) -> dict:
-        """Get model type (element) coverage.
+    def get_observed_types(self) -> dict:
+        """Get observed types (elements) during model training.
 
         Returns
         -------
         dict
-            A dictionary containing the information of type coverage in the model:
-            - 'type_num': the total number of covered types in this model.
-            - 'covered_type': a list of the covered types in this model.
+            A dictionary containing the information of observed type in the model:
+            - 'type_num': the total number of observed types in this model.
+            - 'observed_type': a list of the observed types in this model.
         """
         buffers_dict = dict(self.dp.named_buffers())
         type_map = np.array(self.type_map)
@@ -678,7 +678,7 @@ def get_type_coverage(self) -> dict:
         bias_mask = (np.abs(out_bias) > 1e-6).any(-1)  # 1e-6 for stability
         return {
             "type_num": bias_mask.sum(),
-            "covered_type": sort_element_type(type_map[bias_mask].tolist()),
+            "observed_type": sort_element_type(type_map[bias_mask].tolist()),
         }
 
     def eval_descriptor(

doc/model/show-model-info.md

@@ -17,7 +17,7 @@ dp --pt show <INPUT> <ATTRIBUTES...>
   - `descriptor`: Displays the model descriptor parameters.
   - `fitting-net`: Displays parameters of the fitting network.
   - `size`: (Supported Backends: PyTorch and PaddlePaddle) Shows the parameter counts for various components.
-  - `type-coverage`: (Supported Backends: PyTorch) Shows the type (element) coverage for this model.
+  - `observed-type`: (Supported Backends: PyTorch) Shows the type (element) coverage for this model.
 
 ## Example Usage
 
@@ -61,10 +61,10 @@ Depending on the provided attributes and the model type, the output includes:
 
   - Prints the number of parameters for each component (`descriptor`, `fitting-net`, etc.), as well as the total parameter count.
 
-- **type-coverage**
+- **observed-type**
 
   - Displays the count and list of element types covered by the model.
-  - For multitask models, it shows the type coverage for each branch.
+  - For multitask models, it shows the observed types for each branch.
   - Note: Type coverage reflects the types observed during training data statistics, which may differ from the type map.
 
 ## Example Output
@@ -80,9 +80,9 @@ Parameter counts:
 Parameters in descriptor: 19,350
 Parameters in fitting-net: 119,091
 Parameters in total: 138,441
-The type coverage for this model:
-Number of covered types: 2
-Covered types: ['H', 'O']
+The observed types for this model:
+Number of observed types: 2
+Observed types: ['H', 'O']
 ```
 
 For a multitask model, if `model-branch` is selected, it will additionally display available branches:

source/tests/pt/test_dp_show.py

@@ -47,7 +47,7 @@ def setUp(self) -> None:
 
     def test_checkpoint(self) -> None:
         INPUT = "model.pt"
-        ATTRIBUTES = "type-map descriptor fitting-net size type-coverage"
+        ATTRIBUTES = "type-map descriptor fitting-net size observed-type"
         with redirect_stderr(io.StringIO()) as f:
             run_dp(f"dp --pt show {INPUT} {ATTRIBUTES}")
         results = [
@@ -66,13 +66,13 @@ def test_checkpoint(self) -> None:
         assert "Parameters in descriptor: 19,350" in results[5]
         assert "Parameters in fitting-net: 119,091" in results[6]
         assert "Parameters in total: 138,441" in results[7]
-        assert "The type coverage for this model:" in results[8]
-        assert "Number of covered types: 2" in results[9]
-        assert "Covered types: ['H', 'O']" in results[10]
+        assert "The observed types for this model:" in results[8]
+        assert "Number of observed types: 2" in results[9]
+        assert "Observed types: ['H', 'O']" in results[10]
 
     def test_frozen_model(self) -> None:
         INPUT = "frozen_model.pth"
-        ATTRIBUTES = "type-map descriptor fitting-net size type-coverage"
+        ATTRIBUTES = "type-map descriptor fitting-net size observed-type"
         with redirect_stderr(io.StringIO()) as f:
             run_dp(f"dp --pt show {INPUT} {ATTRIBUTES}")
         results = [
@@ -91,9 +91,9 @@ def test_frozen_model(self) -> None:
         assert "Parameters in descriptor: 19,350" in results[5]
         assert "Parameters in fitting-net: 119,091" in results[6]
         assert "Parameters in total: 138,441" in results[7]
-        assert "The type coverage for this model:" in results[8]
-        assert "Number of covered types: 2" in results[9]
-        assert "Covered types: ['H', 'O']" in results[10]  # only covers two elements
+        assert "The observed types for this model:" in results[8]
+        assert "Number of observed types: 2" in results[9]
+        assert "Observed types: ['H', 'O']" in results[10]  # only covers two elements
 
     def test_checkpoint_error(self) -> None:
         INPUT = "model.pt"
@@ -162,7 +162,7 @@ def setUp(self) -> None:
 
     def test_checkpoint(self) -> None:
         INPUT = "model.ckpt.pt"
-        ATTRIBUTES = "model-branch type-map descriptor fitting-net size type-coverage"
+        ATTRIBUTES = "model-branch type-map descriptor fitting-net size observed-type"
         with redirect_stderr(io.StringIO()) as f:
             run_dp(f"dp --pt show {INPUT} {ATTRIBUTES}")
         results = [
@@ -200,17 +200,17 @@ def test_checkpoint(self) -> None:
         assert "Parameters in descriptor: 19,350" in results[9]
         assert "Parameters in fitting-net: 4,860" in results[10]
         assert "Parameters in total: 24,210" in results[11]
-        assert "The type coverage for each branch:" in results[12]
-        assert "model_1: Number of covered types: 2" in results[13]
-        assert "model_1: Covered types: ['H', 'O']" in results[14]
-        assert "model_2: Number of covered types: 2" in results[15]
-        assert "model_2: Covered types: ['H', 'O']" in results[16]
-        assert "TOTAL number of covered types in the model: 2" in results[17]
-        assert "TOTAL covered types in the model: ['H', 'O']" in results[18]
+        assert "The observed types for each branch:" in results[12]
+        assert "model_1: Number of observed types: 2" in results[13]
+        assert "model_1: Observed types: ['H', 'O']" in results[14]
+        assert "model_2: Number of observed types: 2" in results[15]
+        assert "model_2: Observed types: ['H', 'O']" in results[16]
+        assert "TOTAL number of observed types in the model: 2" in results[17]
+        assert "TOTAL observed types in the model: ['H', 'O']" in results[18]
 
     def test_frozen_model(self) -> None:
         INPUT = "frozen_model.pth"
-        ATTRIBUTES = "type-map descriptor fitting-net size type-coverage"
+        ATTRIBUTES = "type-map descriptor fitting-net size observed-type"
         with redirect_stderr(io.StringIO()) as f:
             run_dp(f"dp --pt show {INPUT} {ATTRIBUTES}")
         results = [
@@ -229,9 +229,9 @@ def test_frozen_model(self) -> None:
         assert "Parameters in descriptor: 19,350" in results[5]
         assert "Parameters in fitting-net: 4,860" in results[6]
         assert "Parameters in total: 24,210" in results[7]
-        assert "The type coverage for this model:" in results[8]
-        assert "Number of covered types: 2" in results[9]
-        assert "Covered types: ['H', 'O']" in results[10]  # only covers two elements
+        assert "The observed types for this model:" in results[8]
+        assert "Number of observed types: 2" in results[9]
+        assert "Observed types: ['H', 'O']" in results[10]  # only covers two elements
 
     def tearDown(self) -> None:
         for f in os.listdir("."):