mirror of https://git.ffmpeg.org/ffmpeg.git
libavfilter/dnn/dnn_backend_tf: add tf.pad support for tensorflow backend with native model.
Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
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@ -27,6 +27,7 @@
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#include "dnn_backend_native.h"
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#include "libavformat/avio.h"
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#include "libavutil/avassert.h"
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#include "dnn_backend_native_layer_pad.h"
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#include <tensorflow/c/c_api.h>
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@ -347,23 +348,8 @@ static DNNReturnType add_depth_to_space_layer(TFModel *tf_model, TF_Operation **
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return DNN_SUCCESS;
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}
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static int calculate_pad(const ConvolutionalNetwork *conv_network)
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{
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ConvolutionalParams *params;
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int32_t layer;
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int pad = 0;
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for (layer = 0; layer < conv_network->layers_num; ++layer){
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if (conv_network->layers[layer].type == CONV){
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params = (ConvolutionalParams *)conv_network->layers[layer].params;
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pad += params->kernel_size >> 1;
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}
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}
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return pad;
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}
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static DNNReturnType add_pad_op(TFModel *tf_model, TF_Operation **cur_op, const int32_t pad)
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static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
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LayerPadParams *params, const int layer)
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{
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TF_Operation *op;
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TF_Tensor *tensor;
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@ -372,16 +358,21 @@ static DNNReturnType add_pad_op(TFModel *tf_model, TF_Operation **cur_op, const
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int32_t *pads;
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int64_t pads_shape[] = {4, 2};
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input.index = 0;
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char name_buffer[NAME_BUFFER_SIZE];
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snprintf(name_buffer, NAME_BUFFER_SIZE, "pad%d", layer);
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op_desc = TF_NewOperation(tf_model->graph, "Const", "pads");
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op_desc = TF_NewOperation(tf_model->graph, "Const", name_buffer);
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TF_SetAttrType(op_desc, "dtype", TF_INT32);
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tensor = TF_AllocateTensor(TF_INT32, pads_shape, 2, 4 * 2 * sizeof(int32_t));
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pads = (int32_t *)TF_TensorData(tensor);
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pads[0] = 0; pads[1] = 0;
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pads[2] = pad; pads[3] = pad;
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pads[4] = pad; pads[5] = pad;
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pads[6] = 0; pads[7] = 0;
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pads[0] = params->paddings[0][0];
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pads[1] = params->paddings[0][1];
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pads[2] = params->paddings[1][0];
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pads[3] = params->paddings[1][1];
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pads[4] = params->paddings[2][0];
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pads[5] = params->paddings[2][1];
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pads[6] = params->paddings[3][0];
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pads[7] = params->paddings[3][1];
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TF_SetAttrTensor(op_desc, "value", tensor, tf_model->status);
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if (TF_GetCode(tf_model->status) != TF_OK){
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return DNN_ERROR;
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@ -393,6 +384,7 @@ static DNNReturnType add_pad_op(TFModel *tf_model, TF_Operation **cur_op, const
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op_desc = TF_NewOperation(tf_model->graph, "MirrorPad", "mirror_pad");
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input.oper = *cur_op;
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input.index = 0;
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TF_AddInput(op_desc, input);
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input.oper = op;
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TF_AddInput(op_desc, input);
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@ -418,7 +410,6 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
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int32_t *transpose_perm;
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int64_t transpose_perm_shape[] = {4};
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int64_t input_shape[] = {1, -1, -1, -1};
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int32_t pad;
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DNNReturnType layer_add_res;
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DNNModel *native_model = NULL;
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ConvolutionalNetwork *conv_network;
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@ -429,7 +420,6 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
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}
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conv_network = (ConvolutionalNetwork *)native_model->model;
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pad = calculate_pad(conv_network);
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tf_model->graph = TF_NewGraph();
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tf_model->status = TF_NewStatus();
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@ -448,10 +438,6 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
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CLEANUP_ON_ERROR(tf_model);
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}
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if (add_pad_op(tf_model, &op, pad) != DNN_SUCCESS){
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CLEANUP_ON_ERROR(tf_model);
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}
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op_desc = TF_NewOperation(tf_model->graph, "Const", "transpose_perm");
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TF_SetAttrType(op_desc, "dtype", TF_INT32);
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tensor = TF_AllocateTensor(TF_INT32, transpose_perm_shape, 1, 4 * sizeof(int32_t));
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@ -479,6 +465,10 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
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layer_add_res = add_depth_to_space_layer(tf_model, &op,
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(DepthToSpaceParams *)conv_network->layers[layer].params, layer);
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break;
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case MIRROR_PAD:
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layer_add_res = add_pad_layer(tf_model, &op,
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(LayerPadParams *)conv_network->layers[layer].params, layer);
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break;
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default:
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CLEANUP_ON_ERROR(tf_model);
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}
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