Renaming uses of optim_ to sparse_ (#189)

kevinaer · web-flow · commit ddeaf1ad9b7e · 2021-04-23T14:09:14.000-04:00
* Added more sparse fixes * adding revertable change * Revert "adding revertable change" This reverts commit c4447b0.
diff --git a/integrations/keras/prune_resnet20.py b/integrations/keras/prune_resnet20.py
@@ -76,9 +76,9 @@ def download_model_and_recipe(root_dir: str):
         repo="sparseml",
         dataset="cifar_10",
         training_scheme=None,
-        optim_name="base",
-        optim_category="none",
-        optim_target=None,
+        sparse_name="base",
+        sparse_category="none",
+        sparse_target=None,
         override_parent_path=model_dir,
     )
     base_zoo_model.download()
diff --git a/integrations/pytorch-torchvision/pruning.ipynb b/integrations/pytorch-torchvision/pruning.ipynb
@@ -280,7 +280,7 @@
     "    framework=\"pytorch\",\n",
     "    repo=\"torchvision\",\n",
     "    dataset=\"imagenette\",\n",
-    "    optim_name=\"pruned\",\n",
+    "    sparse_name=\"pruned\",\n",
     ")[0]  # unwrap search result\n",
     "recipe.download()\n",
     "recipe_path = recipe.downloaded_path()\n",
diff --git a/notebooks/keras_classification.ipynb b/notebooks/keras_classification.ipynb
@@ -80,9 +80,9 @@
     "            repo=\"sparseml\",\n",
     "            dataset=\"mnist\",\n",
     "            training_scheme=None,\n",
-    "            optim_name=\"pruned\",\n",
-    "            optim_category=\"conservative\",\n",
-    "            optim_target=None,\n",
+    "            sparse_name=\"pruned\",\n",
+    "            sparse_category=\"conservative\",\n",
+    "            sparse_target=None,\n",
     "            override_parent_path=model_dir,\n",
     "        )\n",
     "    zoo_model.download()\n",
diff --git a/notebooks/pytorch_classification.ipynb b/notebooks/pytorch_classification.ipynb
@@ -229,7 +229,7 @@
     "    framework=\"pytorch\",\n",
     "    repo=\"sparseml\",\n",
     "    dataset=\"imagenette\",\n",
-    "    optim_name=\"pruned\",\n",
+    "    sparse_name=\"pruned\",\n",
     ")[0]  # unwrap search result\n",
     "recipe.download()\n",
     "recipe_path = recipe.downloaded_path()\n",
diff --git a/notebooks/pytorch_detection.ipynb b/notebooks/pytorch_detection.ipynb
@@ -248,7 +248,7 @@
     "    framework=\"pytorch\",\n",
     "    repo=\"sparseml\",\n",
     "    dataset=\"voc\",\n",
-    "    optim_name=\"pruned\",\n",
+    "    sparse_name=\"pruned\",\n",
     ")[0]  # unwrap search result\n",
     "recipe.download()\n",
     "recipe_path = recipe.downloaded_path()\n",
diff --git a/notebooks/tensorflow_v1_classification.ipynb b/notebooks/tensorflow_v1_classification.ipynb
@@ -181,7 +181,7 @@
     "        framework=\"tensorflow_v1\",\n",
     "        repo=\"sparseml\",\n",
     "        dataset=\"imagenette\",\n",
-    "        optim_name=\"pruned\",\n",
+    "        sparse_name=\"pruned\",\n",
     "    )[0]  # unwrap search result\n",
     "    recipe.download()\n",
     "    \n",
diff --git a/src/sparseml/keras/models/registry.py b/src/sparseml/keras/models/registry.py
@@ -124,7 +124,7 @@ def create_zoo_model(
 
         attributes = ModelRegistry._ATTRIBUTES[key]
 
-        optim_name, optim_category, optim_target = parse_optimization_str(
+        sparse_name, sparse_category, sparse_target = parse_optimization_str(
             pretrained if isinstance(pretrained, str) else attributes.default_desc
         )
 
@@ -139,9 +139,9 @@ def create_zoo_model(
             if pretrained_dataset is None
             else pretrained_dataset,
             None,
-            optim_name,
-            optim_category,
-            optim_target,
+            sparse_name,
+            sparse_category,
+            sparse_target,
         )
 
     @staticmethod
diff --git a/src/sparseml/pytorch/models/registry.py b/src/sparseml/pytorch/models/registry.py
@@ -133,7 +133,7 @@ def create_zoo_model(
 
         attributes = ModelRegistry._ATTRIBUTES[key]
 
-        optim_name, optim_category, optim_target = parse_optimization_str(
+        sparse_name, sparse_category, sparse_target = parse_optimization_str(
             pretrained if isinstance(pretrained, str) else attributes.default_desc
         )
 
@@ -148,9 +148,9 @@ def create_zoo_model(
             if pretrained_dataset is None
             else pretrained_dataset,
             None,
-            optim_name,
-            optim_category,
-            optim_target,
+            sparse_name,
+            sparse_category,
+            sparse_target,
         )
 
     @staticmethod
diff --git a/src/sparseml/tensorflow_v1/models/registry.py b/src/sparseml/tensorflow_v1/models/registry.py
@@ -147,7 +147,7 @@ def create_zoo_model(
             )
 
         attributes = ModelRegistry._ATTRIBUTES[key]
-        optim_name, optim_category, optim_target = parse_optimization_str(
+        sparse_name, sparse_category, sparse_target = parse_optimization_str(
             pretrained if isinstance(pretrained, str) else attributes.default_desc
         )
 
@@ -162,9 +162,9 @@ def create_zoo_model(
             if pretrained_dataset is None
             else pretrained_dataset,
             None,
-            optim_name,
-            optim_category,
-            optim_target,
+            sparse_name,
+            sparse_category,
+            sparse_target,
         )
 
     @staticmethod
diff --git a/src/sparseml/utils/helpers.py b/src/sparseml/utils/helpers.py
@@ -824,13 +824,13 @@ def parse_optimization_str(optim_full_name: str) -> Tuple[str, str, Any]:
     """
     :param optim_full_name: A name of a pretrained model optimization. i.e.
         'pruned-moderate-deepsparse', 'pruned-aggressive', 'base'
-    :return: A tuple representing the corresponding SparseZoo model optim_name,
-        optim_category, and optim_target values with appropriate defaults when
+    :return: A tuple representing the corresponding SparseZoo model sparse_name,
+        sparse_category, and sparse_target values with appropriate defaults when
         not present.
     """
     optim_defaults = ["base", "none", None]
     optim_split_name = optim_full_name.split("-")
     while len(optim_split_name) < len(optim_defaults):
         optim_split_name.append(optim_defaults[len(optim_split_name)])
-    optim_name, optim_category, optim_target = optim_split_name[:3]
-    return optim_name, optim_category, optim_target
+    sparse_name, sparse_category, sparse_target = optim_split_name[:3]
+    return sparse_name, sparse_category, sparse_target
diff --git a/tests/sparseml/onnx/helpers.py b/tests/sparseml/onnx/helpers.py
@@ -759,9 +759,9 @@ def analyzer_models(request):
                 "repo": "sparseml",
                 "dataset": "imagenet",
                 "training_scheme": None,
-                "optim_name": "base",
-                "optim_category": "none",
-                "optim_target": None,
+                "sparse_name": "base",
+                "sparse_category": "none",
+                "sparse_target": None,
             },
             "resnet50",
         ),
@@ -775,9 +775,9 @@ def analyzer_models(request):
                 "repo": "sparseml",
                 "dataset": "imagenet",
                 "training_scheme": None,
-                "optim_name": "base",
-                "optim_category": "none",
-                "optim_target": None,
+                "sparse_name": "base",
+                "sparse_category": "none",
+                "sparse_target": None,
             },
             "mobilenet",
         ),
diff --git a/tests/sparseml/onnx/optim/quantization/test_quantize_model_post_training.py b/tests/sparseml/onnx/optim/quantization/test_quantize_model_post_training.py
@@ -138,9 +138,9 @@ def test_quantize_model_post_training_resnet50_imagenette():
         repo="sparseml",
         dataset="imagenette",
         training_scheme=None,
-        optim_name="base",
-        optim_category="none",
-        optim_target=None,
+        sparse_name="base",
+        sparse_category="none",
+        sparse_target=None,
     ).onnx_file.downloaded_path()
     quant_model_path = tempfile.NamedTemporaryFile(suffix=".onnx", delete=False).name
 
diff --git a/tests/sparseml/onnx/optim/test_analyzer_model.py b/tests/sparseml/onnx/optim/test_analyzer_model.py
@@ -43,9 +43,9 @@
                 "repo": "sparseml",
                 "dataset": "imagenet",
                 "training_scheme": None,
-                "optim_name": "base",
-                "optim_category": "none",
-                "optim_target": None,
+                "sparse_name": "base",
+                "sparse_category": "none",
+                "sparse_target": None,
             },
             "resnet50pytorch.json",
         ),
diff --git a/tests/sparseml/onnx/utils/test_data.py b/tests/sparseml/onnx/utils/test_data.py
@@ -47,9 +47,9 @@
                 "repo": "sparseml",
                 "dataset": "imagenet",
                 "training_scheme": None,
-                "optim_name": "base",
-                "optim_category": "none",
-                "optim_target": None,
+                "sparse_name": "base",
+                "sparse_category": "none",
+                "sparse_target": None,
             },
             {"input": (1, 3, 224, 224)},
             {"output_0": (1, 1000), "output_1": (1, 1000)},
@@ -65,9 +65,9 @@
                 "repo": "sparseml",
                 "dataset": "imagenet",
                 "training_scheme": None,
-                "optim_name": "base",
-                "optim_category": "none",
-                "optim_target": None,
+                "sparse_name": "base",
+                "sparse_category": "none",
+                "sparse_target": None,
             },
             {"input": (1, 3, 224, 224)},
             {"output_0": (1, 1000)},
diff --git a/tests/sparseml/onnx/utils/test_helpers.py b/tests/sparseml/onnx/utils/test_helpers.py
@@ -363,8 +363,8 @@ def test_onnx_node_sparsities():
         architecture="mobilenet_v1",
         dataset="imagenet",
         framework="pytorch",
-        optim_name="pruned",
-        optim_category="moderate",
+        sparse_name="pruned",
+        sparse_category="moderate",
         repo="sparseml",
     )
     assert len(models) > 0
diff --git a/tests/sparseml/onnx/utils/test_models.py b/tests/sparseml/onnx/utils/test_models.py
@@ -53,9 +53,9 @@
                 "repo": "sparseml",
                 "dataset": "imagenet",
                 "training_scheme": None,
-                "optim_name": "base",
-                "optim_category": "none",
-                "optim_target": None,
+                "sparse_name": "base",
+                "sparse_category": "none",
+                "sparse_target": None,
             }
         ),
         (
@@ -68,9 +68,9 @@
                 "repo": "sparseml",
                 "dataset": "imagenet",
                 "training_scheme": None,
-                "optim_name": "base",
-                "optim_category": "none",
-                "optim_target": None,
+                "sparse_name": "base",
+                "sparse_category": "none",
+                "sparse_target": None,
             }
         ),
     ]

Original file line number	Diff line number	Diff line change
`@@ -147,7 +147,7 @@ def create_zoo_model(`
`147`	`147`	`)`
`148`	`148`
`149`	`149`	`attributes = ModelRegistry._ATTRIBUTES[key]`
`150`		`- optim_name, optim_category, optim_target = parse_optimization_str(`
	`150`	`+ sparse_name, sparse_category, sparse_target = parse_optimization_str(`
`151`	`151`	`pretrained if isinstance(pretrained, str) else attributes.default_desc`
`152`	`152`	`)`
`153`	`153`
`@@ -162,9 +162,9 @@ def create_zoo_model(`
`162`	`162`	`if pretrained_dataset is None`
`163`	`163`	`else pretrained_dataset,`
`164`	`164`	`None,`
`165`		`- optim_name,`
`166`		`- optim_category,`
`167`		`- optim_target,`
	`165`	`+ sparse_name,`
	`166`	`+ sparse_category,`
	`167`	`+ sparse_target,`
`168`	`168`	`)`
`169`	`169`
`170`	`170`	`@staticmethod`