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Update on "Add batching rule for "is_complex", "conj""
To unblock #43208, which adds "is_complex" checks to backward formulas that are being tested for batched gradient support with vmap. Test Plan: - `pytest test/test_vmap.py -v` Differential Revision: [D23685356](https://our.internmc.facebook.com/intern/diff/D23685356) [ghstack-poisoned]
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‎.circleci/cimodel/data/caffe2_build_data.py‎

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‎.circleci/cimodel/data/caffe2_build_definitions.py‎

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‎.circleci/cimodel/data/pytorch_build_data.py‎

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

‎.circleci/cimodel/data/pytorch_build_definitions.py‎

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compiler_version = fc.find_prop("compiler_version")
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is_xla = fc.find_prop("is_xla") or False
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is_asan = fc.find_prop("is_asan") or False
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is_onnx = fc.find_prop("is_onnx") or False
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is_pure_torch = fc.find_prop("is_pure_torch") or False
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is_vulkan = fc.find_prop("is_vulkan") or False
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parms_list_ignored_for_docker_image = []
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parms_list[0] = fc.find_prop("abbreviated_pyver")
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restrict_phases = ["build", "test1", "test2"]
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if is_onnx:
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parms_list.append("onnx")
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python_version = fc.find_prop("pyver")
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parms_list[0] = fc.find_prop("abbreviated_pyver")
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restrict_phases = ["build", "ort_test1", "ort_test2"]
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if cuda_version:
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cuda_gcc_version = fc.find_prop("cuda_gcc_override") or "gcc7"
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parms_list.append(cuda_gcc_version)

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

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