Only check that arguments are Variables in VariableType#4943
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colesbury merged 2 commits intopytorch:masterfrom Jan 31, 2018
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Only check that arguments are Variables in VariableType#4943colesbury merged 2 commits intopytorch:masterfrom
colesbury merged 2 commits intopytorch:masterfrom
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Don't check the ScalarType and Backend of arguments in VariableType. Instead, only check that arguments are Variables of any type. The precise type checks are handled by the base type. Many of our functions take heterogeneous types. There isn't enough information in Declarations.yaml to ensure the precise types of arguments in VariableType, which makes it difficult to add new methods.
gchanan
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Jan 30, 2018
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| Tensor & VariableType::unpack_any(const Tensor & t, const char * name, int pos) const { | ||
| Variable & VariableType::checked_cast(const Tensor & t, const char * name, int pos) { |
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* Revert "Clarify grad_input_mask documentation in derivatives.yaml (#4963)" This reverts commit 6f3266b. * Revert "fix triu and tril for zero-strided inputs on gpu (#4962)" This reverts commit 6c197c2. * Revert "Add mutex for CPU RNG and move TH to C++ (#4041)" This reverts commit 96239dd. * Revert "Support multivariate TransformedDistributions (#4937)" This reverts commit ca5071d. * Revert "Only check that arguments are Variables in VariableType (#4943)" This reverts commit d444379. * Revert "torch.set_num_threads sets MKL option too (#4949)" This reverts commit 2aaeec0.
colesbury
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colesbury
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Don't check the ScalarType and Backend of arguments in VariableType. Instead, only check that arguments are Variables of any type. The precise type checks are handled by the base type. Many of our functions take heterogeneous types. There isn't enough information in Declarations.yaml to ensure the precise types of arguments in VariableType, which makes it difficult to add new methods. This is #4943 with a fix to the memset call
laurentdupin
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Apr 24, 2026
Don't check the ScalarType and Backend of arguments in VariableType. Instead, only check that arguments are Variables of any type. The precise type checks are handled by the base type. Many of our functions take heterogeneous types. There isn't enough information in Declarations.yaml to ensure the precise types of arguments in VariableType, which makes it difficult to add new methods.
laurentdupin
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* Revert "Clarify grad_input_mask documentation in derivatives.yaml (pytorch#4963)" This reverts commit 37c8454. * Revert "fix triu and tril for zero-strided inputs on gpu (pytorch#4962)" This reverts commit 9acb9be. * Revert "Add mutex for CPU RNG and move TH to C++ (pytorch#4041)" This reverts commit 07b7fe2. * Revert "Support multivariate TransformedDistributions (pytorch#4937)" This reverts commit 18bdb4a. * Revert "Only check that arguments are Variables in VariableType (pytorch#4943)" This reverts commit a479ca0. * Revert "torch.set_num_threads sets MKL option too (pytorch#4949)" This reverts commit 2cfb339.
laurentdupin
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…rch#4943)" (pytorch#4980) Revert "Only check that arguments are Variables in VariableType (pytorch#4943)"
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Don't check the ScalarType and Backend of arguments in VariableType. Instead, only check that arguments are Variables of any type. The precise type checks are handled by the base type. Many of our functions take heterogeneous types. There isn't enough information in Declarations.yaml to ensure the precise types of arguments in VariableType, which makes it difficult to add new methods. This is pytorch#4943 with a fix to the memset call
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Don't check the ScalarType and Backend of arguments in VariableType.
Instead, only check that arguments are Variables of any type. The
precise type checks are handled by the base type.
Many of our functions take heterogeneous types. There isn't enough
information in Declarations.yaml to ensure the precise types of
arguments in VariableType, which makes it difficult to add new methods.