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libavfilter/dnn/dnn_backend_tf: add tf.pad support for tensorflow backend with native model.

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Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
This commit is contained in:
Guo, Yejun 2019-08-16 10:37:09 +08:00 committed by Pedro Arthur
parent 29aeeb3e3e
commit 67889d4715
1 changed files with 19 additions and 29 deletions
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48
libavfilter/dnn/dnn_backend_tf.c
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@ -27,6 +27,7 @@
#include "dnn_backend_native.h"
#include "libavformat/avio.h"
#include "libavutil/avassert.h"
#include "dnn_backend_native_layer_pad.h"
#include <tensorflow/c/c_api.h>
@ -347,23 +348,8 @@ static DNNReturnType add_depth_to_space_layer(TFModel *tf_model, TF_Operation **
return DNN_SUCCESS;
}
static int calculate_pad(const ConvolutionalNetwork *conv_network)
{
ConvolutionalParams *params;
int32_t layer;
int pad = 0;
for (layer = 0; layer < conv_network->layers_num; ++layer){
if (conv_network->layers[layer].type == CONV){
params = (ConvolutionalParams *)conv_network->layers[layer].params;
pad += params->kernel_size >> 1;
}
}
return pad;
}
static DNNReturnType add_pad_op(TFModel *tf_model, TF_Operation **cur_op, const int32_t pad)
static DNNReturnType add_pad_layer(TFModel *tf_model, TF_Operation **cur_op,
LayerPadParams *params, const int layer)
{
TF_Operation *op;
TF_Tensor *tensor;
@ -372,16 +358,21 @@ static DNNReturnType add_pad_op(TFModel *tf_model, TF_Operation **cur_op, const
int32_t *pads;
int64_t pads_shape[] = {4, 2};
input.index = 0;
char name_buffer[NAME_BUFFER_SIZE];
snprintf(name_buffer, NAME_BUFFER_SIZE, "pad%d", layer);
op_desc = TF_NewOperation(tf_model->graph, "Const", "pads");
op_desc = TF_NewOperation(tf_model->graph, "Const", name_buffer);
TF_SetAttrType(op_desc, "dtype", TF_INT32);
tensor = TF_AllocateTensor(TF_INT32, pads_shape, 2, 4 * 2 * sizeof(int32_t));
pads = (int32_t *)TF_TensorData(tensor);
pads[0] = 0; pads[1] = 0;
pads[2] = pad; pads[3] = pad;
pads[4] = pad; pads[5] = pad;
pads[6] = 0; pads[7] = 0;
pads[0] = params->paddings[0][0];
pads[1] = params->paddings[0][1];
pads[2] = params->paddings[1][0];
pads[3] = params->paddings[1][1];
pads[4] = params->paddings[2][0];
pads[5] = params->paddings[2][1];
pads[6] = params->paddings[3][0];
pads[7] = params->paddings[3][1];
TF_SetAttrTensor(op_desc, "value", tensor, tf_model->status);
if (TF_GetCode(tf_model->status) != TF_OK){
return DNN_ERROR;
@ -393,6 +384,7 @@ static DNNReturnType add_pad_op(TFModel *tf_model, TF_Operation **cur_op, const
op_desc = TF_NewOperation(tf_model->graph, "MirrorPad", "mirror_pad");
input.oper = *cur_op;
input.index = 0;
TF_AddInput(op_desc, input);
input.oper = op;
TF_AddInput(op_desc, input);
@ -418,7 +410,6 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
int32_t *transpose_perm;
int64_t transpose_perm_shape[] = {4};
int64_t input_shape[] = {1, -1, -1, -1};
int32_t pad;
DNNReturnType layer_add_res;
DNNModel *native_model = NULL;
ConvolutionalNetwork *conv_network;
@ -429,7 +420,6 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
}
conv_network = (ConvolutionalNetwork *)native_model->model;
pad = calculate_pad(conv_network);
tf_model->graph = TF_NewGraph();
tf_model->status = TF_NewStatus();
@ -448,10 +438,6 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
CLEANUP_ON_ERROR(tf_model);
}
if (add_pad_op(tf_model, &op, pad) != DNN_SUCCESS){
CLEANUP_ON_ERROR(tf_model);
}
op_desc = TF_NewOperation(tf_model->graph, "Const", "transpose_perm");
TF_SetAttrType(op_desc, "dtype", TF_INT32);
tensor = TF_AllocateTensor(TF_INT32, transpose_perm_shape, 1, 4 * sizeof(int32_t));
@ -479,6 +465,10 @@ static DNNReturnType load_native_model(TFModel *tf_model, const char *model_file
layer_add_res = add_depth_to_space_layer(tf_model, &op,
(DepthToSpaceParams *)conv_network->layers[layer].params, layer);
break;
case MIRROR_PAD:
layer_add_res = add_pad_layer(tf_model, &op,
(LayerPadParams *)conv_network->layers[layer].params, layer);
break;
default:
CLEANUP_ON_ERROR(tf_model);
}