Update on "[pytorch] Add triplet margin loss with custom distance"

Summary: As discussed [here](#43342),
adding in a Python-only implementation of the triplet-margin loss that takes a
custom distance function.  Still discussing whether this is necessary to add to
PyTorch Core.

Test Plan: python test/run_tests.py

Reviewers:

Subscribers:

Tasks:

Tags:

Differential Revision: [D23363898](https://our.internmc.facebook.com/intern/diff/D23363898)

[ghstack-poisoned]

.circleci/cimodel/data/pytorch_build_data.py

@@ -21,6 +21,11 @@
                     ("asan", [XImportant(True)]),
                 ]),
             ]),
+            ("7", [
+                ("3.6", [
+                    ("onnx", [XImportant(True)]),
+                ]),
+            ]),
         ]),
         ("cuda", [
             ("9.2", [
@@ -149,6 +154,7 @@ def child_constructor(self):
             "vulkan": VulkanConfigNode,
             "parallel_tbb": ParallelTBBConfigNode,
             "parallel_native": ParallelNativeConfigNode,
+            "onnx": ONNXConfigNode,
             "libtorch": LibTorchConfigNode,
             "important": ImportantConfigNode,
             "build_only": BuildOnlyConfigNode,
@@ -192,6 +198,17 @@ def child_constructor(self):
         return ImportantConfigNode
 
 
+class ONNXConfigNode(TreeConfigNode):
+    def modify_label(self, label):
+        return "Onnx=" + str(label)
+
+    def init2(self, node_name):
+        self.props["is_onnx"] = node_name
+
+    def child_constructor(self):
+        return ImportantConfigNode
+
+
 class VulkanConfigNode(TreeConfigNode):
     def modify_label(self, label):
         return "Vulkan=" + str(label)

.circleci/cimodel/data/pytorch_build_definitions.py

@@ -263,6 +263,7 @@ def instantiate_configs():
         compiler_version = fc.find_prop("compiler_version")
         is_xla = fc.find_prop("is_xla") or False
         is_asan = fc.find_prop("is_asan") or False
+        is_onnx = fc.find_prop("is_onnx") or False
         is_pure_torch = fc.find_prop("is_pure_torch") or False
         is_vulkan = fc.find_prop("is_vulkan") or False
         parms_list_ignored_for_docker_image = []
@@ -302,6 +303,12 @@ def instantiate_configs():
             parms_list[0] = fc.find_prop("abbreviated_pyver")
             restrict_phases = ["build", "test1", "test2"]
 
+        if is_onnx:
+            parms_list.append("onnx")
+            python_version = fc.find_prop("pyver")
+            parms_list[0] = fc.find_prop("abbreviated_pyver")
+            restrict_phases = ["build", "ort_test1", "ort_test2"]
+
         if cuda_version:
             cuda_gcc_version = fc.find_prop("cuda_gcc_override") or "gcc7"
             parms_list.append(cuda_gcc_version)

.circleci/cimodel/data/simple/anaconda_prune_defintions.py

@@ -0,0 +1,28 @@
+from collections import OrderedDict
+
+from cimodel.data.simple.util.branch_filters import gen_filter_dict
+from cimodel.lib.miniutils import quote
+
+
+CHANNELS_TO_PRUNE = ["pytorch-nightly", "pytorch-test"]
+PACKAGES_TO_PRUNE = "pytorch torchvision torchaudio torchtext ignite torchcsprng"
+
+
+def gen_workflow_job(channel: str):
+    return OrderedDict(
+        {
+            "anaconda_prune": OrderedDict(
+                {
+                    "name": f"anaconda-prune-{channel}",
+                    "context": quote("org-member"),
+                    "packages": quote(PACKAGES_TO_PRUNE),
+                    "channel": channel,
+                    "filters": gen_filter_dict(branches_list=["postnightly"]),
+                }
+            )
+        }
+    )
+
+
+def get_workflow_jobs():
+    return [gen_workflow_job(channel) for channel in CHANNELS_TO_PRUNE]

.circleci/cimodel/data/simple/docker_definitions.py

@@ -20,14 +20,13 @@
     "pytorch-linux-xenial-cuda9.2-cudnn7-py3-gcc7",
     "pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
     "pytorch-linux-xenial-py3-clang5-asan",
+    "pytorch-linux-xenial-py3-clang7-onnx",
     "pytorch-linux-xenial-py3.8",
     "pytorch-linux-xenial-py3.6-clang7",
     "pytorch-linux-xenial-py3.6-gcc4.8",
     "pytorch-linux-xenial-py3.6-gcc5.4",
     "pytorch-linux-xenial-py3.6-gcc7.2",
     "pytorch-linux-xenial-py3.6-gcc7",
-    "pytorch-linux-xenial-rocm3.3-py3.6",
-    "pytorch-linux-xenial-rocm3.5.1-py3.6",
     "pytorch-linux-bionic-rocm3.7-py3.6",
 ]