Searched refs:kernel_size_ (Results 1 – 12 of 12) sorted by relevance
/third_party/mindspore/mindspore/ccsrc/minddata/dataset/kernels/ir/vision/ |
D | gaussian_blur_ir.cc | 25 : kernel_size_(kernel_size), sigma_(sigma) {} in GaussianBlurOperation() 32 RETURN_IF_NOT_OK(ValidateVectorSize("GaussianBlur", kernel_size_)); in ValidateParams() 33 RETURN_IF_NOT_OK(ValidateVectorOdd("GaussianBlur", "kernel_size", kernel_size_)); in ValidateParams() 39 int32_t kernel_x = kernel_size_[0]; in Build() 40 int32_t kernel_y = kernel_size_[0]; in Build() 42 if (kernel_size_.size() == 2) { in Build() 43 kernel_y = kernel_size_[1]; in Build() 59 args["kernel_size"] = kernel_size_; in to_json()
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D | gaussian_blur_ir.h | 52 std::vector<int32_t> kernel_size_;
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/third_party/mindspore/mindspore/ccsrc/frontend/parallel/ops_info/ |
D | maxpool_info.cc | 33 kernel_size_ = GetTupleIntAttr(KERNEL_SIZE); in GetAttrs() 34 if (kernel_size_.size() != 4) { in GetAttrs() 35 … MS_LOG(ERROR) << name_ << ": The size of kernel_size must be 4, but got " << kernel_size_.size(); in GetAttrs() 39 if (kernel_size_[0] != 1 || kernel_size_[1] != 1) { in GetAttrs() 40 … name_ << ": The first two elements of kernel_size must be 1, but got (" << kernel_size_[0] << ", " in GetAttrs() 41 << kernel_size_[1] << ")"; in GetAttrs() 72 …MS_LOG(INFO) << name_ << ": The kernel size is " << kernel_size_ << ", pad mode is " << pad_mode_ … in GetAttrs() 94 if (kernel_size_[2] > stride_[2]) { in CheckHWStrategy() 109 if (kernel_size_[3] > stride_[3]) { in CheckHWStrategy()
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D | conv2d_info.cc | 73 kernel_size_ = {kernel_size, kernel_size}; in GetAttrsBase() 75 kernel_size_ = GetValue<std::vector<int64_t>>(kernel_size_iter->second); in GetAttrsBase() 76 if (kernel_size_.size() != 2) { in GetAttrsBase() 77 …OG(ERROR) << name_ << ": The size of kernel_size'tuple must be 2, but got " << kernel_size_.size(); in GetAttrsBase() 129 …OG(INFO) << name_ << ": The out channel is " << out_channel_ << ", kernel size is " << kernel_size_ in GetAttrsBase() 162 if (kernel_size_[0] > stride_[2] && h_strategy > 1) { in CheckHWStrategySameMode() 167 if (h_strategy > 1 && (kernel_size_[0] <= stride_[2] && h_slice_shape % stride_[2] != 0)) { in CheckHWStrategySameMode() 175 if (w_strategy > 1 && (kernel_size_[1] <= stride_[3] && w_slice_shape % stride_[3] != 0)) { in CheckHWStrategySameMode() 182 if (w_strategy > 1 && (kernel_size_[1] > stride_[3])) { in CheckHWStrategySameMode() 190 if (w_slice_shape <= ((kernel_size_[1] - stride_[3] + 1) / 2)) { in CheckHWStrategySameMode() [all …]
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D | maxpool_info.h | 53 std::vector<int64_t> kernel_size_; // four integers
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D | conv2d_info.h | 69 std::vector<int64_t> kernel_size_; // two integers variable
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/third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/mkldnn/ |
D | pooling_max_grad_cpu_kernel.cc | 54 kernel_size_ = {IntToSize(kernel_sizes[2]), IntToSize(kernel_sizes[3])}; in InitKernel() 58 …GetPadding(kernel_node, pad_mode, src_shape_, kernel_size_, stride_, &padding_l_, &padding_r, dumm… in InitKernel() 99 box[0].second = IntToSize(std::min(h_start + SizeToInt(kernel_size_[0]), src_height)); in ChannelPoolingGrad() 107 box[1].second = IntToSize(std::min(w_start + SizeToInt(kernel_size_[1]), src_width)); in ChannelPoolingGrad()
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D | pooling_avg_grad_cpu_kernel.h | 38 std::vector<size_t> kernel_size_;
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D | pooling_max_grad_cpu_kernel.h | 42 std::vector<size_t> kernel_size_; variable
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/third_party/mindspore/mindspore/lite/src/delegate/tensorrt/op/ |
D | pool_tensorrt.cc | 71 nvinfer1::Dims windowSize = lite::ConvertCudaDims(kernel_size_); in AddInnerOp() 113 kernel_size_ = std::vector<int64_t>(kernel_size->begin(), kernel_size->end()); in ParseParams() 146 kernel_size_ = std::vector<int64_t>(kernel_size->begin(), kernel_size->end()); in ParseParams()
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D | pool_tensorrt.h | 41 std::vector<int64_t> kernel_size_; variable
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/third_party/mindspore/mindspore/ccsrc/minddata/dataset/api/ |
D | vision.cc | 353 : kernel_size_(kernel_size), sigma_(sigma) {} in Data() 354 std::vector<int32_t> kernel_size_; member 362 return std::make_shared<GaussianBlurOperation>(data_->kernel_size_, data_->sigma_); in Parse()
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