From: Vitaly Fedyunin Date: Thu, 13 Dec 2018 19:32:06 +0000 (-0800) Subject: Kill non-forward, non-backward functions generated from nn.yaml (#15127) X-Git-Tag: accepted/tizen/6.5/unified/20211028.231830~2266 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=e5bd6fe86d6eb07ae3544696aec3ba2e3ced8e85;p=platform%2Fupstream%2Fpytorch.git Kill non-forward, non-backward functions generated from nn.yaml (#15127) Summary: Updating binding to legacy functions. Remove unused declarations. Pull Request resolved: https://github.com/pytorch/pytorch/pull/15127 Differential Revision: D13433405 Pulled By: VitalyFedyunin fbshipit-source-id: 58544d38affd20818742338c9eb789d9d14ccbaa --- diff --git a/aten/src/ATen/native/LegacyNNDefinitions.cpp b/aten/src/ATen/native/LegacyNNDefinitions.cpp index 62dac43..2c02746 100644 --- a/aten/src/ATen/native/LegacyNNDefinitions.cpp +++ b/aten/src/ATen/native/LegacyNNDefinitions.cpp @@ -5,10 +5,10 @@ namespace at { namespace native { Tensor & binary_cross_entropy_out(Tensor & output, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction) { - return at::legacy::th::_thnn_binary_cross_entropy_out(output, self, target, weight, reduction); + return at::legacy::th::_thnn_binary_cross_entropy_forward_out(output, self, target, weight, reduction); } Tensor binary_cross_entropy(const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction) { - return at::legacy::th::_thnn_binary_cross_entropy(self, target, weight, reduction); + return at::legacy::th::_thnn_binary_cross_entropy_forward(self, target, weight, reduction); } Tensor & binary_cross_entropy_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction) { return at::legacy::th::_thnn_binary_cross_entropy_backward_out(grad_input, grad_output, self, target, weight, reduction); @@ -19,11 +19,11 @@ Tensor binary_cross_entropy_backward(const Tensor & grad_output, const Tensor & } Tensor & mse_loss_out(Tensor & output, const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_mse_loss_out(output, self, target, reduction); + return at::legacy::th::_thnn_mse_loss_forward_out(output, self, target, reduction); } Tensor mse_loss(const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_mse_loss(self, target, reduction); + return at::legacy::th::_thnn_mse_loss_forward(self, target, reduction); } Tensor & mse_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, int64_t reduction) { @@ -35,11 +35,11 @@ Tensor mse_loss_backward(const Tensor & grad_output, const Tensor & self, const } Tensor & l1_loss_out(Tensor & output, const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_l1_loss_out(output, self, target, reduction); + return at::legacy::th::_thnn_l1_loss_forward_out(output, self, target, reduction); } Tensor l1_loss(const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_l1_loss(self, target, reduction); + return at::legacy::th::_thnn_l1_loss_forward(self, target, reduction); } Tensor & l1_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, int64_t reduction) { @@ -52,12 +52,12 @@ Tensor l1_loss_backward(const Tensor & grad_output, const Tensor & self, const T Tensor & multi_margin_loss_out(Tensor & output, const Tensor & self, const Tensor & target, Scalar p, Scalar margin, const Tensor & weight, int64_t reduction) { - return at::legacy::th::_thnn_multi_margin_loss_out(output, self, target, p, margin, weight, reduction); + return at::legacy::th::_thnn_multi_margin_loss_forward_out(output, self, target, p, margin, weight, reduction); } Tensor multi_margin_loss(const Tensor & self, const Tensor & target, Scalar p, Scalar margin, const Tensor & weight, int64_t reduction) { - return at::legacy::th::_thnn_multi_margin_loss(self, target, p, margin, weight, reduction); + return at::legacy::th::_thnn_multi_margin_loss_forward(self, target, p, margin, weight, reduction); } Tensor & multi_margin_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, @@ -146,11 +146,11 @@ Tensor nll_loss2d_backward(const Tensor & grad_output, const Tensor & self, cons } Tensor & smooth_l1_loss_out(Tensor & output, const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_smooth_l1_loss_out(output, self, target, reduction); + return at::legacy::th::_thnn_smooth_l1_loss_forward_out(output, self, target, reduction); } Tensor smooth_l1_loss(const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_smooth_l1_loss(self, target, reduction); + return at::legacy::th::_thnn_smooth_l1_loss_forward(self, target, reduction); } Tensor & smooth_l1_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, @@ -163,11 +163,11 @@ Tensor smooth_l1_loss_backward(const Tensor & grad_output, const Tensor & self, } Tensor & soft_margin_loss_out(Tensor & output, const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_soft_margin_loss_out(output, self, target, reduction); + return at::legacy::th::_thnn_soft_margin_loss_forward_out(output, self, target, reduction); } Tensor soft_margin_loss(const Tensor & self, const Tensor & target, int64_t reduction) { - return at::legacy::th::_thnn_soft_margin_loss(self, target, reduction); + return at::legacy::th::_thnn_soft_margin_loss_forward(self, target, reduction); } Tensor & soft_margin_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, @@ -180,11 +180,11 @@ Tensor soft_margin_loss_backward(const Tensor & grad_output, const Tensor & self } Tensor & elu_out(Tensor & output, const Tensor & self, Scalar alpha, Scalar scale, Scalar input_scale) { - return at::legacy::th::_thnn_elu_out(output, self, alpha, scale, input_scale); + return at::legacy::th::_thnn_elu_forward_out(output, self, alpha, scale, input_scale); } Tensor elu(const Tensor & self, Scalar alpha, Scalar scale, Scalar input_scale) { - return at::legacy::th::_thnn_elu(self, alpha, scale, input_scale); + return at::legacy::th::_thnn_elu_forward(self, alpha, scale, input_scale); } Tensor & elu_backward_out(Tensor & grad_input, const Tensor & grad_output, Scalar alpha, Scalar scale, Scalar input_scale, const Tensor & output) { @@ -196,15 +196,15 @@ Tensor elu_backward(const Tensor & grad_output, Scalar alpha, Scalar scale, Scal } Tensor & elu_(Tensor & self, Scalar alpha, Scalar scale, Scalar input_scale) { - return at::legacy::th::_thnn_elu_(self, alpha, scale, input_scale); + return at::legacy::th::_thnn_elu_forward_(self, alpha, scale, input_scale); } Tensor & glu_out(Tensor & output, const Tensor & self, int64_t dim) { - return at::legacy::th::_thnn_glu_out(output, self, dim); + return at::legacy::th::_thnn_glu_forward_out(output, self, dim); } Tensor glu(const Tensor & self, int64_t dim) { - return at::legacy::th::_thnn_glu(self, dim); + return at::legacy::th::_thnn_glu_forward(self, dim); } Tensor & glu_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, int64_t dim) { @@ -216,11 +216,11 @@ Tensor glu_backward(const Tensor & grad_output, const Tensor & self, int64_t dim } Tensor & hardtanh_out(Tensor & output, const Tensor & self, Scalar min_val, Scalar max_val) { - return at::legacy::th::_thnn_hardtanh_out(output, self, min_val, max_val); + return at::legacy::th::_thnn_hardtanh_forward_out(output, self, min_val, max_val); } Tensor hardtanh(const Tensor & self, Scalar min_val, Scalar max_val) { - return at::legacy::th::_thnn_hardtanh(self, min_val, max_val); + return at::legacy::th::_thnn_hardtanh_forward(self, min_val, max_val); } Tensor & hardtanh_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, Scalar min_val, Scalar max_val) { @@ -232,15 +232,15 @@ Tensor hardtanh_backward(const Tensor & grad_output, const Tensor & self, Scalar } Tensor & hardtanh_(Tensor & self, Scalar min_val, Scalar max_val) { - return at::legacy::th::_thnn_hardtanh_(self, min_val, max_val); + return at::legacy::th::_thnn_hardtanh_forward_(self, min_val, max_val); } Tensor & leaky_relu_out(Tensor & output, const Tensor & self, Scalar negative_slope) { - return at::legacy::th::_thnn_leaky_relu_out(output, self, negative_slope); + return at::legacy::th::_thnn_leaky_relu_forward_out(output, self, negative_slope); } Tensor leaky_relu(const Tensor & self, Scalar negative_slope) { - return at::legacy::th::_thnn_leaky_relu(self, negative_slope); + return at::legacy::th::_thnn_leaky_relu_forward(self, negative_slope); } Tensor & leaky_relu_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, Scalar negative_slope) { @@ -252,7 +252,7 @@ Tensor leaky_relu_backward(const Tensor & grad_output, const Tensor & self, Scal } Tensor & leaky_relu_(Tensor & self, Scalar negative_slope) { - return at::legacy::th::_thnn_leaky_relu_(self, negative_slope); + return at::legacy::th::_thnn_leaky_relu_forward_(self, negative_slope); } Tensor & log_sigmoid_out(Tensor & output, const Tensor & self) { @@ -281,11 +281,11 @@ Tensor log_sigmoid_backward(const Tensor & grad_output, const Tensor & self, con } Tensor & rrelu_with_noise_out(Tensor & output, const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, Generator * generator) { - return at::legacy::th::_thnn_rrelu_with_noise_out(output, self, noise, lower, upper, training, generator); + return at::legacy::th::_thnn_rrelu_with_noise_forward_out(output, self, noise, lower, upper, training, generator); } Tensor rrelu_with_noise(const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, Generator * generator) { - return at::legacy::th::_thnn_rrelu_with_noise(self, noise, lower, upper, training, generator); + return at::legacy::th::_thnn_rrelu_with_noise_forward(self, noise, lower, upper, training, generator); } Tensor & rrelu_with_noise_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training) { @@ -297,15 +297,15 @@ Tensor rrelu_with_noise_backward(const Tensor & grad_output, const Tensor & self } Tensor & rrelu_with_noise_(Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, Generator * generator) { - return at::legacy::th::_thnn_rrelu_with_noise_(self, noise, lower, upper, training, generator); + return at::legacy::th::_thnn_rrelu_with_noise_forward_(self, noise, lower, upper, training, generator); } Tensor & softplus_out(Tensor & output, const Tensor & self, Scalar beta, Scalar threshold) { - return at::legacy::th::_thnn_softplus_out(output, self, beta, threshold); + return at::legacy::th::_thnn_softplus_forward_out(output, self, beta, threshold); } Tensor softplus(const Tensor & self, Scalar beta, Scalar threshold) { - return at::legacy::th::_thnn_softplus(self, beta, threshold); + return at::legacy::th::_thnn_softplus_forward(self, beta, threshold); } Tensor & softplus_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, Scalar beta, Scalar threshold, const Tensor & output) { @@ -317,11 +317,11 @@ Tensor softplus_backward(const Tensor & grad_output, const Tensor & self, Scalar } Tensor & softshrink_out(Tensor & output, const Tensor & self, Scalar lambd) { - return at::legacy::th::_thnn_softshrink_out(output, self, lambd); + return at::legacy::th::_thnn_softshrink_forward_out(output, self, lambd); } Tensor softshrink(const Tensor & self, Scalar lambd) { - return at::legacy::th::_thnn_softshrink(self, lambd); + return at::legacy::th::_thnn_softshrink_forward(self, lambd); } Tensor & softshrink_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, Scalar lambd) { @@ -333,11 +333,11 @@ Tensor softshrink_backward(const Tensor & grad_output, const Tensor & self, Scal } Tensor & adaptive_avg_pool3d_out(Tensor & output, const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_adaptive_avg_pool3d_out(output, self, output_size); + return at::legacy::th::_thnn_adaptive_avg_pool3d_forward_out(output, self, output_size); } Tensor adaptive_avg_pool3d(const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_adaptive_avg_pool3d(self, output_size); + return at::legacy::th::_thnn_adaptive_avg_pool3d_forward(self, output_size); } Tensor & adaptive_avg_pool3d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self) { @@ -349,11 +349,11 @@ Tensor adaptive_avg_pool3d_backward(const Tensor & grad_output, const Tensor & s } std::tuple adaptive_max_pool2d_out(Tensor & output, Tensor & indices, const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_adaptive_max_pool2d_out(output, indices, self, output_size); + return at::legacy::th::_thnn_adaptive_max_pool2d_forward_out(output, indices, self, output_size); } std::tuple adaptive_max_pool2d(const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_adaptive_max_pool2d(self, output_size); + return at::legacy::th::_thnn_adaptive_max_pool2d_forward(self, output_size); } Tensor & adaptive_max_pool2d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & indices) { @@ -365,11 +365,11 @@ Tensor adaptive_max_pool2d_backward(const Tensor & grad_output, const Tensor & s } std::tuple adaptive_max_pool3d_out(Tensor & output, Tensor & indices, const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_adaptive_max_pool3d_out(output, indices, self, output_size); + return at::legacy::th::_thnn_adaptive_max_pool3d_forward_out(output, indices, self, output_size); } std::tuple adaptive_max_pool3d(const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_adaptive_max_pool3d(self, output_size); + return at::legacy::th::_thnn_adaptive_max_pool3d_forward(self, output_size); } Tensor & adaptive_max_pool3d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & indices) { @@ -381,11 +381,11 @@ Tensor adaptive_max_pool3d_backward(const Tensor & grad_output, const Tensor & s } Tensor & avg_pool2d_out(Tensor & output, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, bool ceil_mode, bool count_include_pad) { - return at::legacy::th::_thnn_avg_pool2d_out(output, self, kernel_size, stride, padding, ceil_mode, count_include_pad); + return at::legacy::th::_thnn_avg_pool2d_forward_out(output, self, kernel_size, stride, padding, ceil_mode, count_include_pad); } Tensor avg_pool2d(const Tensor & self, IntList kernel_size, IntList stride, IntList padding, bool ceil_mode, bool count_include_pad) { - return at::legacy::th::_thnn_avg_pool2d(self, kernel_size, stride, padding, ceil_mode, count_include_pad); + return at::legacy::th::_thnn_avg_pool2d_forward(self, kernel_size, stride, padding, ceil_mode, count_include_pad); } Tensor & avg_pool2d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, bool ceil_mode, bool count_include_pad) { @@ -397,11 +397,11 @@ Tensor avg_pool2d_backward(const Tensor & grad_output, const Tensor & self, IntL } Tensor & avg_pool3d_out(Tensor & output, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, bool ceil_mode, bool count_include_pad) { - return at::legacy::th::_thnn_avg_pool3d_out(output, self, kernel_size, stride, padding, ceil_mode, count_include_pad); + return at::legacy::th::_thnn_avg_pool3d_forward_out(output, self, kernel_size, stride, padding, ceil_mode, count_include_pad); } Tensor avg_pool3d(const Tensor & self, IntList kernel_size, IntList stride, IntList padding, bool ceil_mode, bool count_include_pad) { - return at::legacy::th::_thnn_avg_pool3d(self, kernel_size, stride, padding, ceil_mode, count_include_pad); + return at::legacy::th::_thnn_avg_pool3d_forward(self, kernel_size, stride, padding, ceil_mode, count_include_pad); } Tensor & avg_pool3d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, bool ceil_mode, bool count_include_pad) { @@ -413,11 +413,11 @@ Tensor avg_pool3d_backward(const Tensor & grad_output, const Tensor & self, IntL } std::tuple fractional_max_pool2d_out(Tensor & output, Tensor & indices, const Tensor & self, IntList kernel_size, IntList output_size, const Tensor & random_samples) { - return at::legacy::th::_thnn_fractional_max_pool2d_out(output, indices, self, kernel_size, output_size, random_samples); + return at::legacy::th::_thnn_fractional_max_pool2d_forward_out(output, indices, self, kernel_size, output_size, random_samples); } std::tuple fractional_max_pool2d(const Tensor & self, IntList kernel_size, IntList output_size, const Tensor & random_samples) { - return at::legacy::th::_thnn_fractional_max_pool2d(self, kernel_size, output_size, random_samples); + return at::legacy::th::_thnn_fractional_max_pool2d_forward(self, kernel_size, output_size, random_samples); } Tensor & fractional_max_pool2d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList kernel_size, IntList output_size, const Tensor & indices) { @@ -429,11 +429,11 @@ Tensor fractional_max_pool2d_backward(const Tensor & grad_output, const Tensor & } std::tuple max_pool2d_with_indices_out(Tensor & output, Tensor & indices, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, IntList dilation, bool ceil_mode) { - return at::legacy::th::_thnn_max_pool2d_with_indices_out(output, indices, self, kernel_size, stride, padding, dilation, ceil_mode); + return at::legacy::th::_thnn_max_pool2d_with_indices_forward_out(output, indices, self, kernel_size, stride, padding, dilation, ceil_mode); } std::tuple max_pool2d_with_indices(const Tensor & self, IntList kernel_size, IntList stride, IntList padding, IntList dilation, bool ceil_mode) { - return at::legacy::th::_thnn_max_pool2d_with_indices(self, kernel_size, stride, padding, dilation, ceil_mode); + return at::legacy::th::_thnn_max_pool2d_with_indices_forward(self, kernel_size, stride, padding, dilation, ceil_mode); } Tensor & max_pool2d_with_indices_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, IntList dilation, bool ceil_mode, const Tensor & indices) { @@ -445,11 +445,11 @@ Tensor max_pool2d_with_indices_backward(const Tensor & grad_output, const Tensor } std::tuple max_pool3d_with_indices_out(Tensor & output, Tensor & indices, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, IntList dilation, bool ceil_mode) { - return at::legacy::th::_thnn_max_pool3d_with_indices_out(output, indices, self, kernel_size, stride, padding, dilation, ceil_mode); + return at::legacy::th::_thnn_max_pool3d_with_indices_forward_out(output, indices, self, kernel_size, stride, padding, dilation, ceil_mode); } std::tuple max_pool3d_with_indices(const Tensor & self, IntList kernel_size, IntList stride, IntList padding, IntList dilation, bool ceil_mode) { - return at::legacy::th::_thnn_max_pool3d_with_indices(self, kernel_size, stride, padding, dilation, ceil_mode); + return at::legacy::th::_thnn_max_pool3d_with_indices_forward(self, kernel_size, stride, padding, dilation, ceil_mode); } Tensor & max_pool3d_with_indices_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList kernel_size, IntList stride, IntList padding, IntList dilation, bool ceil_mode, const Tensor & indices) { @@ -461,11 +461,11 @@ Tensor max_pool3d_with_indices_backward(const Tensor & grad_output, const Tensor } Tensor & max_unpool2d_out(Tensor & output, const Tensor & self, const Tensor & indices, IntList output_size) { - return at::legacy::th::_thnn_max_unpool2d_out(output, self, indices, output_size); + return at::legacy::th::_thnn_max_unpool2d_forward_out(output, self, indices, output_size); } Tensor max_unpool2d(const Tensor & self, const Tensor & indices, IntList output_size) { - return at::legacy::th::_thnn_max_unpool2d(self, indices, output_size); + return at::legacy::th::_thnn_max_unpool2d_forward(self, indices, output_size); } Tensor & max_unpool2d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & indices, IntList output_size) { @@ -477,11 +477,11 @@ Tensor max_unpool2d_backward(const Tensor & grad_output, const Tensor & self, co } Tensor & max_unpool3d_out(Tensor & output, const Tensor & self, const Tensor & indices, IntList output_size, IntList stride, IntList padding) { - return at::legacy::th::_thnn_max_unpool3d_out(output, self, indices, output_size, stride, padding); + return at::legacy::th::_thnn_max_unpool3d_forward_out(output, self, indices, output_size, stride, padding); } Tensor max_unpool3d(const Tensor & self, const Tensor & indices, IntList output_size, IntList stride, IntList padding) { - return at::legacy::th::_thnn_max_unpool3d(self, indices, output_size, stride, padding); + return at::legacy::th::_thnn_max_unpool3d_forward(self, indices, output_size, stride, padding); } Tensor & max_unpool3d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & indices, IntList output_size, IntList stride, IntList padding) { @@ -493,11 +493,11 @@ Tensor max_unpool3d_backward(const Tensor & grad_output, const Tensor & self, co } Tensor & reflection_pad1d_out(Tensor & output, const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_reflection_pad1d_out(output, self, padding); + return at::legacy::th::_thnn_reflection_pad1d_forward_out(output, self, padding); } Tensor reflection_pad1d(const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_reflection_pad1d(self, padding); + return at::legacy::th::_thnn_reflection_pad1d_forward(self, padding); } Tensor & reflection_pad1d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList padding) { @@ -509,11 +509,11 @@ Tensor reflection_pad1d_backward(const Tensor & grad_output, const Tensor & self } Tensor & reflection_pad2d_out(Tensor & output, const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_reflection_pad2d_out(output, self, padding); + return at::legacy::th::_thnn_reflection_pad2d_forward_out(output, self, padding); } Tensor reflection_pad2d(const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_reflection_pad2d(self, padding); + return at::legacy::th::_thnn_reflection_pad2d_forward(self, padding); } Tensor & reflection_pad2d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList padding) { @@ -525,11 +525,11 @@ Tensor reflection_pad2d_backward(const Tensor & grad_output, const Tensor & self } Tensor & replication_pad1d_out(Tensor & output, const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_replication_pad1d_out(output, self, padding); + return at::legacy::th::_thnn_replication_pad1d_forward_out(output, self, padding); } Tensor replication_pad1d(const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_replication_pad1d(self, padding); + return at::legacy::th::_thnn_replication_pad1d_forward(self, padding); } Tensor & replication_pad1d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList padding) { @@ -541,11 +541,11 @@ Tensor replication_pad1d_backward(const Tensor & grad_output, const Tensor & sel } Tensor & replication_pad2d_out(Tensor & output, const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_replication_pad2d_out(output, self, padding); + return at::legacy::th::_thnn_replication_pad2d_forward_out(output, self, padding); } Tensor replication_pad2d(const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_replication_pad2d(self, padding); + return at::legacy::th::_thnn_replication_pad2d_forward(self, padding); } Tensor & replication_pad2d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList padding) { @@ -557,11 +557,11 @@ Tensor replication_pad2d_backward(const Tensor & grad_output, const Tensor & sel } Tensor & replication_pad3d_out(Tensor & output, const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_replication_pad3d_out(output, self, padding); + return at::legacy::th::_thnn_replication_pad3d_forward_out(output, self, padding); } Tensor replication_pad3d(const Tensor & self, IntList padding) { - return at::legacy::th::_thnn_replication_pad3d(self, padding); + return at::legacy::th::_thnn_replication_pad3d_forward(self, padding); } Tensor & replication_pad3d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, IntList padding) { @@ -573,11 +573,11 @@ Tensor replication_pad3d_backward(const Tensor & grad_output, const Tensor & sel } Tensor & upsample_linear1d_out(Tensor & output, const Tensor & self, IntList output_size, bool align_corners) { - return at::legacy::th::_thnn_upsample_linear1d_out(output, self, output_size, align_corners); + return at::legacy::th::_thnn_upsample_linear1d_forward_out(output, self, output_size, align_corners); } Tensor upsample_linear1d(const Tensor & self, IntList output_size, bool align_corners) { - return at::legacy::th::_thnn_upsample_linear1d(self, output_size, align_corners); + return at::legacy::th::_thnn_upsample_linear1d_forward(self, output_size, align_corners); } Tensor & upsample_linear1d_backward_out(Tensor & grad_input, const Tensor & grad_output, IntList output_size, IntList input_size, bool align_corners) { @@ -589,11 +589,11 @@ Tensor upsample_linear1d_backward(const Tensor & grad_output, IntList output_siz } Tensor & upsample_bilinear2d_out(Tensor & output, const Tensor & self, IntList output_size, bool align_corners) { - return at::legacy::th::_thnn_upsample_bilinear2d_out(output, self, output_size, align_corners); + return at::legacy::th::_thnn_upsample_bilinear2d_forward_out(output, self, output_size, align_corners); } Tensor upsample_bilinear2d(const Tensor & self, IntList output_size, bool align_corners) { - return at::legacy::th::_thnn_upsample_bilinear2d(self, output_size, align_corners); + return at::legacy::th::_thnn_upsample_bilinear2d_forward(self, output_size, align_corners); } Tensor & upsample_bilinear2d_backward_out(Tensor & grad_input, const Tensor & grad_output, IntList output_size, IntList input_size, bool align_corners) { @@ -605,11 +605,11 @@ Tensor upsample_bilinear2d_backward(const Tensor & grad_output, IntList output_s } Tensor & upsample_trilinear3d_out(Tensor & output, const Tensor & self, IntList output_size, bool align_corners) { - return at::legacy::th::_thnn_upsample_trilinear3d_out(output, self, output_size, align_corners); + return at::legacy::th::_thnn_upsample_trilinear3d_forward_out(output, self, output_size, align_corners); } Tensor upsample_trilinear3d(const Tensor & self, IntList output_size, bool align_corners) { - return at::legacy::th::_thnn_upsample_trilinear3d(self, output_size, align_corners); + return at::legacy::th::_thnn_upsample_trilinear3d_forward(self, output_size, align_corners); } Tensor & upsample_trilinear3d_backward_out(Tensor & grad_input, const Tensor & grad_output, IntList output_size, IntList input_size, bool align_corners) { @@ -621,11 +621,11 @@ Tensor upsample_trilinear3d_backward(const Tensor & grad_output, IntList output_ } Tensor & upsample_nearest1d_out(Tensor & output, const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_upsample_nearest1d_out(output, self, output_size); + return at::legacy::th::_thnn_upsample_nearest1d_forward_out(output, self, output_size); } Tensor upsample_nearest1d(const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_upsample_nearest1d(self, output_size); + return at::legacy::th::_thnn_upsample_nearest1d_forward(self, output_size); } Tensor & upsample_nearest1d_backward_out(Tensor & grad_input, const Tensor & grad_output, IntList output_size, IntList input_size) { @@ -637,11 +637,11 @@ Tensor upsample_nearest1d_backward(const Tensor & grad_output, IntList output_si } Tensor & upsample_nearest2d_out(Tensor & output, const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_upsample_nearest2d_out(output, self, output_size); + return at::legacy::th::_thnn_upsample_nearest2d_forward_out(output, self, output_size); } Tensor upsample_nearest2d(const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_upsample_nearest2d(self, output_size); + return at::legacy::th::_thnn_upsample_nearest2d_forward(self, output_size); } Tensor & upsample_nearest2d_backward_out(Tensor & grad_input, const Tensor & grad_output, IntList output_size, IntList input_size) { @@ -653,11 +653,11 @@ Tensor upsample_nearest2d_backward(const Tensor & grad_output, IntList output_si } Tensor & upsample_nearest3d_out(Tensor & output, const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_upsample_nearest3d_out(output, self, output_size); + return at::legacy::th::_thnn_upsample_nearest3d_forward_out(output, self, output_size); } Tensor upsample_nearest3d(const Tensor & self, IntList output_size) { - return at::legacy::th::_thnn_upsample_nearest3d(self, output_size); + return at::legacy::th::_thnn_upsample_nearest3d_forward(self, output_size); } Tensor & upsample_nearest3d_backward_out(Tensor & grad_input, const Tensor & grad_output, IntList output_size, IntList input_size) { diff --git a/aten/src/ATen/nn_parse.py b/aten/src/ATen/nn_parse.py index 49e96e7..3930ccc 100644 --- a/aten/src/ATen/nn_parse.py +++ b/aten/src/ATen/nn_parse.py @@ -407,7 +407,6 @@ def run(paths): bwd_functions.append(header_functions[cname + suffix]) base = base_declaration(func, fwd_function, backends) - declarations.append(base) declarations.append(forward_declaration(base, fwd_function)) declarations.append(backward_declaration(base, bwd_functions))