| /third_party/mindspore/mindspore/ops/_op_impl/_custom_op/ |
| D | batchnorm_fold_grad.py | 57 def _batchnorm_fold_grad_compute(d_batch_mean, d_batch_std, data_x, batch_mean, batch_std): argument
77 def batchnorm_fold_grad(d_batch_mean, d_batch_std, x, batch_mean, batch_std, dx, argument
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| D | batchnorm_fold2.py | 58 def batchnorm_fold2_compute(x, beta, gamma, batch_std, batch_mean, running_std, kernel_name="batchn… argument
73 def batchnorm_fold2(x, beta, gamma, batch_std, batch_mean, running_std, y, kernel_name="batchnorm_f… argument
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| D | batchnorm_fold2_grad.py | 57 def batchnorm_fold2_grad_compute(dout, dout_reduce, dout_x_reduce, gamma, batch_std, batch_mean, ru… argument
84 def batchnorm_fold2_grad(dout, dout_reduce, dout_x_reduce, gamma, batch_std, batch_mean, running_st… argument
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| D | batchnorm_fold.py | 101 … y, batch_mean, batch_std, running_mean, running_std, mean_updated, variance_updated, argument
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| /third_party/mindspore/tests/st/ops/gpu/ |
| D | test_batchnorm_fold_grad_op.py | 34 def construct(self, d_batch_mean, d_batch_std, x, batch_mean, batch_std, current_step): argument
39 def np_result(d_batch_mean, d_batch_std, x, batch_mean, batch_std): argument
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| D | test_batchnorm_fold2_op.py | 35 …def construct(self, x, beta, gamma, batch_std, batch_mean, running_std, running_mean, current_step… argument
47 …def construct(self, x, beta, gamma, batch_std, batch_mean, running_std, running_mean, current_step… argument
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/ |
| D | batchnorm_fold2_impl.cu | 28 …NormFold2Kernel(const T *x, const T *beta, const T *gamma, const T *batch_std, const T *batch_mean, in BatchNormFold2Kernel()
67 __global__ void BatchNormFold2GradNotFreeze(const T *d_beta, const T *reduce_x, const T *batch_mean… in BatchNormFold2GradNotFreeze()
104 …ormFold2Forward(const T *x, const T *beta, const T *gamma, const T *batch_std, const T *batch_mean, in BatchNormFold2Forward()
132 void CalBatchNormFold2GradNotFreeze(const T *d_beta, const T *reduce_x, const T *batch_mean, const … in CalBatchNormFold2GradNotFreeze()
146 void CalBatchNormFold2GradFreeze(const T *d_beta, const T *reduce_x, const T *batch_mean, const T *… in CalBatchNormFold2GradFreeze()
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| D | batchnorm_fold_impl.cu | 40 __global__ void CalDx(const T* d_batch_mean, const T* d_batch_std, const T* x, const T* batch_mean,… in CalDx()
70 … CalBatchNormFoldGrad(const T* d_batch_mean, const T* d_batch_std, const T* x, const T* batch_mean, in CalBatchNormFoldGrad()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/quant/ |
| D | batchnorm_fold2_gpu_kernel.h | 56 auto *batch_mean = GetDeviceAddress<T>(inputs, 4); in Launch() local
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| D | batchnorm_fold_grad_gpu_kernel.h | 60 T *batch_mean = GetDeviceAddress<T>(inputs, 3); in Launch() local
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| D | batchnorm_fold_gpu_kernel.h | 70 auto batch_mean = GetDeviceAddress<T>(outputs, 0); in Launch() local
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| D | batchnorm_fold2_grad_gpu_kernel.h | 56 auto *batch_mean = GetDeviceAddress<T>(inputs, 4); in Launch() local
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| /third_party/mindspore/mindspore/ops/_grad/ |
| D | grad_quant_ops.py | 118 …def bprop(x, beta, gamma, batch_std, batch_mean, running_std, running_mean, global_step, out, dout… argument
155 def bprop(x, beta, gamma, batch_std, batch_mean, running_std, out, dout): argument
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| /third_party/mindspore/mindspore/ops/operations/ |
| D | _grad_ops.py | 701 def infer_shape(self, grads, x, diff_scale, diff_offset, scale, batch_mean, batch_variance): argument
704 def infer_dtype(self, grads, x, diff_scale, diff_offset, scale, batch_mean, batch_variance): argument
716 def infer_shape(self, grads, x, batch_mean, batch_variance): argument
719 def infer_dtype(self, grads, x, batch_mean, batch_variance): argument
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