Searched refs:k_size (Results 1 – 6 of 6) sorted by relevance
| /third_party/mindspore/mindspore/ccsrc/backend/optimizer/ascend/mindir/ |
| D | avg_pool_grad_unify_mindir.cc | 101 … const std::vector<int64_t> &k_size, const std::vector<int64_t> &stride, in CreateMeanMatrixValueNode() argument
106 …if (x_shape.size() != kShapeDimNum || k_size.size() != kShapeDimNum || stride.size() != kShapeDimN… in CreateMeanMatrixValueNode()
108 << x_shape << ", kernel_size:" << k_size << ", strides:" << stride; in CreateMeanMatrixValueNode()
112 …windowed_output_size(x_shape[kDim2], k_size[kDim2], stride[kDim2], pad_mode, &pad_top, &pad_bottom… in CreateMeanMatrixValueNode()
114 …windowed_output_size(x_shape[kDim3], k_size[kDim3], stride[kDim3], pad_mode, &pad_left, &pad_right… in CreateMeanMatrixValueNode()
122 for (int64_t i = h * stride[kDim2]; i < h * stride[kDim2] + k_size[kDim2]; ++i) { in CreateMeanMatrixValueNode()
123 for (int64_t j = w * stride[kDim3]; j < w * stride[kDim3] + k_size[kDim3]; ++j) { in CreateMeanMatrixValueNode()
157 const std::vector<int64_t> &k_size, const TypeId x_dtype) { in CreateKernelMatrixValueNode() argument
161 if (x_shape.size() != kShapeDimNum || k_size.size() != kShapeDimNum) { in CreateKernelMatrixValueNode()
163 << ", kernel_size:" << k_size; in CreateKernelMatrixValueNode()
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| /third_party/ffmpeg/libavformat/ |
| D | omadec.c | 79 uint16_t k_size; member
154 size < OMA_ENC_HEADER_SIZE + oc->k_size + oc->e_size + oc->i_size || in rprobe()
171 pos = OMA_ENC_HEADER_SIZE + oc->k_size + oc->e_size; in rprobe()
191 size < OMA_ENC_HEADER_SIZE + oc->k_size + 4) in nprobe()
194 pos = OMA_ENC_HEADER_SIZE + oc->k_size; in nprobe()
265 oc->k_size = AV_RB16(&gdata[2]); in decrypt_init()
274 if (OMA_ENC_HEADER_SIZE + oc->k_size + oc->e_size + oc->i_size + 8 > geob->datasize || in decrypt_init()
286 &gdata[OMA_ENC_HEADER_SIZE + oc->k_size + oc->e_size + oc->i_size], in decrypt_init()
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| /third_party/boost/boost/numeric/ublas/ |
| D | operation_blocked.hpp | 155 size_type k_size = BOOST_UBLAS_SAME (e1 ().size2 (), e2 ().size1 ()); in block_prod() local
168 for (size_type k_begin = 0; k_begin < k_size; k_begin += block_size) { in block_prod()
169 size_type k_end = k_begin + (std::min) (k_size - k_begin, block_size); in block_prod()
216 size_type k_size = BOOST_UBLAS_SAME (e1 ().size2 (), e2 ().size1 ()); in block_prod() local
229 for (size_type k_begin = 0; k_begin < k_size; k_begin += block_size) { in block_prod()
230 size_type k_end = k_begin + (std::min) (k_size - k_begin, block_size); in block_prod()
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| /third_party/mindspore/mindspore/core/ops/grad/ |
| D | pool_grad.cc | 58 std::vector<int64_t> k_size = _grad_check_vector(kKernelSize, kernel_size, this->name()); in set_kernel_size() local
59 (void)this->AddAttr(kKernelSize, MakeValue(k_size)); in set_kernel_size()
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| /third_party/mindspore/mindspore/ccsrc/backend/optimizer/ascend/ir_fusion/ |
| D | avgpool_3d_grad_fusion.cc | 81 bool IsVectorImpl(const std::vector<int64_t> &fp_shape, const std::vector<int64_t> &k_size, in IsVectorImpl() argument
87 auto kd = k_size[kDim0]; in IsVectorImpl()
88 auto kh = k_size[kDim1]; in IsVectorImpl()
89 auto kw = k_size[kDim2]; in IsVectorImpl()
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| /third_party/mindspore/mindspore/ops/operations/ |
| D | _inner_ops.py | 1343 k_size = (q[1], q[0], q[3], q[2])
1345 return q, k_size
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