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@ -271,9 +271,9 @@ void ConvWinogardFp32(float *input_data, float *trans_weight, const float *bias_
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int out_h_block = UP_DIV(conv_param->output_h_, out_unit);
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int output_count = out_w_block * out_h_block;
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#ifdef ENABLE_ARM32
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int tile_num = 4;
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const int tile_num = 4;
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#else
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int tile_num = 12;
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const int tile_num = 12;
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#endif
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int output_tile_count = UP_DIV(output_count, tile_num);
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int out_channel = conv_param->output_channel_;
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@ -470,9 +470,9 @@ void Conv3x3Fp32(float *input_data, float *transed_weight, const float *bias_dat
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int out_h_block = UP_DIV(conv_param->output_h_, OUPUT_UNIT);
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int output_count = out_w_block * out_h_block;
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#ifdef ENABLE_ARM32
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int tile_num = 4;
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const int tile_num = 4;
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#else
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int tile_num = 12;
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const int tile_num = 12;
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#endif
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int output_tile_count = UP_DIV(output_count, tile_num);
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const int input_unit_square = 4 * 4;
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@ -41,9 +41,9 @@ int DeConvPostFp32C12x8(const float *src, float *tmp, const float *bias, float *
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size_t output_plane = conv_param->output_w_ * conv_param->output_h_;
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int oc8 = UP_ROUND(output_channel, C8NUM);
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#ifdef ENABLE_ARM32
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int tile_num = 4;
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const int tile_num = 4;
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#else
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int tile_num = 12;
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const int tile_num = 12;
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#endif
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int in_plane12 = UP_ROUND(input_plane, tile_num);
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int src_iw_stride = C8NUM;
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@ -55,8 +55,8 @@ void DecodeBoxes(const int num_boxes, const float *input_boxes, const float *anc
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BboxCorner *decoded_box = (BboxCorner *)(decoded_boxes) + i;
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float y_center = box->y / scaler.y * anchor->h + anchor->y;
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float x_center = box->x / scaler.x * anchor->w + anchor->x;
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float h_half = 0.5f * expf(box->h / scaler.h) * anchor->h;
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float w_half = 0.5f * expf(box->w / scaler.w) * anchor->w;
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const float h_half = 0.5f * expf(box->h / scaler.h) * anchor->h;
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const float w_half = 0.5f * expf(box->w / scaler.w) * anchor->w;
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decoded_box->ymin = y_center - h_half;
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decoded_box->xmin = x_center - w_half;
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decoded_box->ymax = y_center + h_half;
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@ -68,9 +68,9 @@ void WinogradInputTransform(const float *input_data, float *trans_input, float *
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}
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// input transform
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#ifdef ENABLE_ARM32
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int tile_num = 4;
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const int tile_num = 4;
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#else
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int tile_num = 12;
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const int tile_num = 12;
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#endif
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int dst_ic4_offset = dst_plane_offset + ic * C4NUM;
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size_t dst_step = tile_num * ic4 * C4NUM;
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@ -337,9 +337,9 @@ void Conv3x3Fp32InputTransform(const float *input_data, float *trans_input, floa
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// input transform
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#ifdef ENABLE_ARM32
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int tile_num = 4;
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const int tile_num = 4;
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#else
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int tile_num = 12;
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const int tile_num = 12;
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#endif
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int dst_ic4_offset = dst_plane_offset + ic * C4NUM;
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size_t dst_step = tile_num * ic4 * C4NUM;
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@ -51,6 +51,7 @@ int ConvolutionWinogradFP16CPUKernel::WinogradFilterTransformFp16(const float16_
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}
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auto matrix_gt_data_fp16 = reinterpret_cast<float16_t *>(malloc(input_unit_ * kernel_unit_ * sizeof(float16_t)));
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if (matrix_gt_data_fp16 == nullptr) {
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free(matrix_g_data_fp16);
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MS_LOG(ERROR) << "malloc matrix_gt_data_fp16 failed.";
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return RET_ERROR;
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}
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@ -61,16 +62,25 @@ int ConvolutionWinogradFP16CPUKernel::WinogradFilterTransformFp16(const float16_
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// separate into two steps ===> tmp = G*g ===> out = tmp * GT
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auto tmp_weight_data = reinterpret_cast<float16_t *>(malloc(kernel_unit_ * kernel_unit_ * sizeof(float16_t)));
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if (tmp_weight_data == nullptr) {
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free(matrix_g_data_fp16);
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free(matrix_gt_data_fp16);
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MS_LOG(ERROR) << "malloc tmp_weight_data failed.";
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return RET_ERROR;
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}
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auto tmp_data = reinterpret_cast<float16_t *>(malloc(input_unit_ * kernel_unit_ * sizeof(float16_t)));
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if (tmp_data == nullptr) {
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free(tmp_weight_data);
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free(matrix_g_data_fp16);
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free(matrix_gt_data_fp16);
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MS_LOG(ERROR) << "malloc tmp_data failed.";
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return RET_ERROR;
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}
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auto trans_out_data = reinterpret_cast<float16_t *>(malloc(input_unit_ * input_unit_ * sizeof(float16_t)));
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if (trans_out_data == nullptr) {
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free(tmp_data);
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free(tmp_weight_data);
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free(matrix_g_data_fp16);
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free(matrix_gt_data_fp16);
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MS_LOG(ERROR) << "malloc trans_out_data failed.";
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return RET_ERROR;
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}
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@ -206,11 +216,14 @@ int ConvolutionWinogradFP16CPUKernel::InitWeightBias() {
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}
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auto matrix_gt = reinterpret_cast<float *>(malloc(input_unit_ * kernel_unit_ * sizeof(float)));
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if (matrix_gt == nullptr) {
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free(matrix_g);
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MS_LOG(ERROR) << "malloc matrix_gt failed.";
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return RET_ERROR;
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}
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ret = MallocTransformMatrices();
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if (ret != RET_OK) {
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free(matrix_g);
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free(matrix_gt);
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MS_LOG(ERROR) << "Malloc transform matrices failed.";
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return ret;
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}
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@ -221,6 +234,8 @@ int ConvolutionWinogradFP16CPUKernel::InitWeightBias() {
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float matrix_bt[MAX_LEN];
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ret = CookToomFilter(matrix_a, matrix_at, matrix_b, matrix_bt, matrix_g, matrix_gt, 0.5f, output_unit_, kernel_unit_);
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if (ret != RET_OK) {
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free(matrix_g);
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free(matrix_gt);
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MS_LOG(ERROR) << "get matrix g from CookToomFilter failed.";
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return ret;
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}
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@ -235,6 +250,8 @@ int ConvolutionWinogradFP16CPUKernel::InitWeightBias() {
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ret = WinogradFilterTransformFp16(execute_weight_, matrix_g, matrix_gt, oc_block);
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if (ret != RET_OK) {
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free(matrix_g);
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free(matrix_gt);
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MS_LOG(ERROR) << "winograd filter transfrom failed.";
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return ret;
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}
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@ -242,6 +259,8 @@ int ConvolutionWinogradFP16CPUKernel::InitWeightBias() {
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// init bias
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bias_data_ = malloc(oc_block_num * oc_block * sizeof(float16_t));
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if (bias_data_ == nullptr) {
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free(matrix_g);
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free(matrix_gt);
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MS_LOG(ERROR) << "malloc bias_data_ failed.";
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return RET_ERROR;
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}
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@ -200,7 +200,7 @@ int MatmulFP16CPUKernel::Run() {
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}
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auto b = reinterpret_cast<float *>(in_tensors_[1]->MutableData());
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auto out_tensor = out_tensors_[0];
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float16_t *c_ptr;
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float16_t *c_ptr = nullptr;
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if (out_tensor->data_type() == kNumberTypeFloat32) {
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c_ptr = output_ptr_;
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} else {
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@ -96,9 +96,9 @@ int Convolution3x3CPUKernel::InitTmpBuffer() {
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MS_ASSERT(ctx_->allocator != nullptr);
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#ifdef ENABLE_ARM32
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int tile_num = 4;
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const int tile_num = 4;
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#else
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int tile_num = 12;
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const int tile_num = 12;
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#endif
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size_t nhwc4_input_size =
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ic4 * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float);
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@ -47,11 +47,14 @@ int ConvolutionWinogradCPUKernel::WinogradFilterTransform(const float *weight_da
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}
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auto tmp_data = reinterpret_cast<float *>(malloc(input_unit_ * kernel_unit_ * sizeof(float)));
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if (tmp_data == nullptr) {
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free(tmp_weight_data);
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MS_LOG(ERROR) << "malloc tmp_data failed.";
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return RET_MEMORY_FAILED;
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}
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auto trans_out_data = reinterpret_cast<float *>(malloc(input_unit_ * input_unit_ * sizeof(float)));
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if (trans_out_data == nullptr) {
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free(tmp_data);
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free(tmp_weight_data);
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MS_LOG(ERROR) << "malloc trans_out_data failed.";
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return RET_MEMORY_FAILED;
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}
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@ -149,7 +149,7 @@ int ReduceCPUKernel::Run() {
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int ReduceCPUKernel::MallocTmpBuffer() {
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data_buffers_.clear();
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for (auto size : buffer_sizes_) {
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void *buffer;
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void *buffer = nullptr;
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if (data_type_ == kDataTypeFloat) {
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buffer = context_->allocator->Malloc(size * sizeof(float));
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} else {
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@ -143,6 +143,7 @@ int SqueezeInt8CPUKernel::Run() {
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auto input_size = quant_Squeeze_parm_->input_sizes_[i];
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inputs_array[i] = reinterpret_cast<int8_t *>(malloc(sizeof(int8_t) * input_size));
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if (inputs_array[i] == nullptr) {
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free(inputs_array);
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MS_LOG(ERROR) << "malloc inputs_array[" << i << "]"
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<< " failed.";
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return RET_ERROR;
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