fix: env formatiing (#379)

Author: sasha-gitg

google/cloud/aiplatform/training_jobs.py

@@ -2121,7 +2121,10 @@ def _run(
                 spec["pythonPackageSpec"]["args"] = args
 
             if environment_variables:
-                spec["pythonPackageSpec"]["env"] = environment_variables
+                spec["pythonPackageSpec"]["env"] = [
+                    {"name": key, "value": value}
+                    for key, value in environment_variables.items()
+                ]
 
         (
             training_task_inputs,
@@ -2671,7 +2674,10 @@ def _run(
                 spec["containerSpec"]["args"] = args
 
             if environment_variables:
-                spec["containerSpec"]["env"] = environment_variables
+                spec["containerSpec"]["env"] = [
+                    {"name": key, "value": value}
+                    for key, value in environment_variables.items()
+                ]
 
         (
             training_task_inputs,
@@ -3734,7 +3740,7 @@ def run(
         Args:
             dataset (Union[datasets.ImageDataset,datasets.TabularDataset,datasets.TextDataset,datasets.VideoDataset,]):
                 AI Platform to fit this training against. Custom training script should
-                retrieve datasets through passed in environement variables uris:
+                retrieve datasets through passed in environment variables uris:
 
                 os.environ["AIP_TRAINING_DATA_URI"]
                 os.environ["AIP_VALIDATION_DATA_URI"]
@@ -3984,7 +3990,10 @@ def _run(
                 spec["pythonPackageSpec"]["args"] = args
 
             if environment_variables:
-                spec["pythonPackageSpec"]["env"] = environment_variables
+                spec["pythonPackageSpec"]["env"] = [
+                    {"name": key, "value": value}
+                    for key, value in environment_variables.items()
+                ]
 
         (
             training_task_inputs,

tests/unit/aiplatform/test_training_jobs.py

@@ -622,7 +622,10 @@ def test_run_call_pipeline_service_create_with_tabular_dataset(
         )
 
         true_args = _TEST_RUN_ARGS
-        true_env = _TEST_ENVIRONMENT_VARIABLES
+        true_env = [
+            {"name": key, "value": value}
+            for key, value in _TEST_ENVIRONMENT_VARIABLES.items()
+        ]
 
         true_worker_pool_spec = {
             "replicaCount": _TEST_REPLICA_COUNT,
@@ -777,7 +780,10 @@ def test_run_call_pipeline_service_create_with_bigquery_destination(
             model_from_job.wait()
 
         true_args = _TEST_RUN_ARGS
-        true_env = _TEST_ENVIRONMENT_VARIABLES
+        true_env = [
+            {"name": key, "value": value}
+            for key, value in _TEST_ENVIRONMENT_VARIABLES.items()
+        ]
 
         true_worker_pool_spec = {
             "replicaCount": _TEST_REPLICA_COUNT,
@@ -1049,7 +1055,10 @@ def test_run_call_pipeline_service_create_with_no_dataset(
         )
 
         true_args = _TEST_RUN_ARGS
-        true_env = _TEST_ENVIRONMENT_VARIABLES
+        true_env = [
+            {"name": key, "value": value}
+            for key, value in _TEST_ENVIRONMENT_VARIABLES.items()
+        ]
 
         true_worker_pool_spec = {
             "replicaCount": _TEST_REPLICA_COUNT,
@@ -1297,7 +1306,10 @@ def test_run_call_pipeline_service_create_distributed_training(
         )
 
         true_args = _TEST_RUN_ARGS
-        true_env = _TEST_ENVIRONMENT_VARIABLES
+        true_env = [
+            {"name": key, "value": value}
+            for key, value in _TEST_ENVIRONMENT_VARIABLES.items()
+        ]
 
         true_worker_pool_spec = [
             {
@@ -1763,7 +1775,10 @@ def test_run_call_pipeline_service_create_with_tabular_dataset(
             model_from_job.wait()
 
         true_args = _TEST_RUN_ARGS
-        true_env = _TEST_ENVIRONMENT_VARIABLES
+        true_env = [
+            {"name": key, "value": value}
+            for key, value in _TEST_ENVIRONMENT_VARIABLES.items()
+        ]
 
         true_worker_pool_spec = {
             "replicaCount": _TEST_REPLICA_COUNT,
@@ -2972,7 +2987,10 @@ def test_run_call_pipeline_service_create_with_tabular_dataset(
             model_from_job.wait()
 
         true_args = _TEST_RUN_ARGS
-        true_env = _TEST_ENVIRONMENT_VARIABLES
+        true_env = [
+            {"name": key, "value": value}
+            for key, value in _TEST_ENVIRONMENT_VARIABLES.items()
+        ]
 
         true_worker_pool_spec = {
             "replicaCount": _TEST_REPLICA_COUNT,