Re: [FFmpeg-devel] [PATCH V2 3/3] dnn: convert tf.pad to native model in python script, and load/execute it in the c code.

2019-07-29 Thread Pedro Arthur 
LGTM.
Pushed, thanks!

Em dom, 28 de jul de 2019 às 23:00, Guo, Yejun  escreveu:
>
> since tf.pad is enabled, the conv2d(valid) changes back to its original 
> behavior.
>
> Signed-off-by: Guo, Yejun 
> ---
>  libavfilter/dnn/dnn_backend_native.c| 35 
> +
>  libavfilter/dnn/dnn_backend_native.h|  2 +-
>  tools/python/convert_from_tensorflow.py | 23 +-
>  3 files changed, 54 insertions(+), 6 deletions(-)
>
> diff --git a/libavfilter/dnn/dnn_backend_native.c 
> b/libavfilter/dnn/dnn_backend_native.c
> index 82e900b..09c583b 100644
> --- a/libavfilter/dnn/dnn_backend_native.c
> +++ b/libavfilter/dnn/dnn_backend_native.c
> @@ -25,6 +25,7 @@
>
>  #include "dnn_backend_native.h"
>  #include "libavutil/avassert.h"
> +#include "dnn_backend_native_layer_pad.h"
>
>  static DNNReturnType set_input_output_native(void *model, DNNInputData 
> *input, const char *input_name, const char **output_names, uint32_t nb_output)
>  {
> @@ -32,6 +33,7 @@ static DNNReturnType set_input_output_native(void *model, 
> DNNInputData *input, c
>  InputParams *input_params;
>  ConvolutionalParams *conv_params;
>  DepthToSpaceParams *depth_to_space_params;
> +LayerPadParams *pad_params;
>  int cur_width, cur_height, cur_channels;
>  int32_t layer;
>
> @@ -77,6 +79,12 @@ static DNNReturnType set_input_output_native(void *model, 
> DNNInputData *input, c
>  cur_height *= depth_to_space_params->block_size;
>  cur_width *= depth_to_space_params->block_size;
>  break;
> +case MIRROR_PAD:
> +pad_params = (LayerPadParams *)network->layers[layer].params;
> +cur_height = cur_height + pad_params->paddings[1][0] + 
> pad_params->paddings[1][1];
> +cur_width = cur_width + pad_params->paddings[2][0] + 
> pad_params->paddings[2][1];
> +cur_channels = cur_channels + pad_params->paddings[3][0] + 
> pad_params->paddings[3][1];
> +break;
>  default:
>  return DNN_ERROR;
>  }
> @@ -110,6 +118,7 @@ DNNModel *ff_dnn_load_model_native(const char 
> *model_filename)
>  DNNLayerType layer_type;
>  ConvolutionalParams *conv_params;
>  DepthToSpaceParams *depth_to_space_params;
> +LayerPadParams *pad_params;
>
>  model = av_malloc(sizeof(DNNModel));
>  if (!model){
> @@ -207,6 +216,23 @@ DNNModel *ff_dnn_load_model_native(const char 
> *model_filename)
>  network->layers[layer].type = DEPTH_TO_SPACE;
>  network->layers[layer].params = depth_to_space_params;
>  break;
> +case MIRROR_PAD:
> +pad_params = av_malloc(sizeof(LayerPadParams));
> +if (!pad_params){
> +avio_closep(_file_context);
> +ff_dnn_free_model_native();
> +return NULL;
> +}
> +pad_params->mode = (int32_t)avio_rl32(model_file_context);
> +dnn_size += 4;
> +for (i = 0; i < 4; ++i) {
> +pad_params->paddings[i][0] = avio_rl32(model_file_context);
> +pad_params->paddings[i][1] = avio_rl32(model_file_context);
> +dnn_size += 8;
> +}
> +network->layers[layer].type = MIRROR_PAD;
> +network->layers[layer].params = pad_params;
> +break;
>  default:
>  avio_closep(_file_context);
>  ff_dnn_free_model_native();
> @@ -314,6 +340,7 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel 
> *model, DNNData *output
>  InputParams *input_params;
>  ConvolutionalParams *conv_params;
>  DepthToSpaceParams *depth_to_space_params;
> +LayerPadParams *pad_params;
>
>  if (network->layers_num <= 0 || network->layers[0].type != INPUT || 
> !network->layers[0].output){
>  return DNN_ERROR;
> @@ -348,6 +375,14 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel 
> *model, DNNData *output
>  cur_width *= depth_to_space_params->block_size;
>  cur_channels /= depth_to_space_params->block_size * 
> depth_to_space_params->block_size;
>  break;
> +case MIRROR_PAD:
> +pad_params = (LayerPadParams *)network->layers[layer].params;
> +dnn_execute_layer_pad(network->layers[layer - 1].output, 
> network->layers[layer].output,
> +  pad_params, 1, cur_height, cur_width, 
> cur_channels);
> +cur_height = cur_height + pad_params->paddings[1][0] + 
> pad_params->paddings[1][1];
> +cur_width = cur_width + pad_params->paddings[2][0] + 
> pad_params->paddings[2][1];
> +cur_channels = cur_channels + pad_params->paddings[3][0] + 
> pad_params->paddings[3][1];
> +break;
>  case INPUT:
>  return DNN_ERROR;
>  }
> diff --git a/libavfilter/dnn/dnn_backend_native.h 
> b/libavfilter/dnn/dnn_backend_native.h
> index

[FFmpeg-devel] [PATCH V2 3/3] dnn: convert tf.pad to native model in python script, and load/execute it in the c code.

2019-07-28 Thread Guo, Yejun 
since tf.pad is enabled, the conv2d(valid) changes back to its original 
behavior.

Signed-off-by: Guo, Yejun 
---
 libavfilter/dnn/dnn_backend_native.c| 35 +
 libavfilter/dnn/dnn_backend_native.h|  2 +-
 tools/python/convert_from_tensorflow.py | 23 +-
 3 files changed, 54 insertions(+), 6 deletions(-)

diff --git a/libavfilter/dnn/dnn_backend_native.c 
b/libavfilter/dnn/dnn_backend_native.c
index 82e900b..09c583b 100644
--- a/libavfilter/dnn/dnn_backend_native.c
+++ b/libavfilter/dnn/dnn_backend_native.c
@@ -25,6 +25,7 @@
 
 #include "dnn_backend_native.h"
 #include "libavutil/avassert.h"
+#include "dnn_backend_native_layer_pad.h"
 
 static DNNReturnType set_input_output_native(void *model, DNNInputData *input, 
const char *input_name, const char **output_names, uint32_t nb_output)
 {
@@ -32,6 +33,7 @@ static DNNReturnType set_input_output_native(void *model, 
DNNInputData *input, c
 InputParams *input_params;
 ConvolutionalParams *conv_params;
 DepthToSpaceParams *depth_to_space_params;
+LayerPadParams *pad_params;
 int cur_width, cur_height, cur_channels;
 int32_t layer;
 
@@ -77,6 +79,12 @@ static DNNReturnType set_input_output_native(void *model, 
DNNInputData *input, c
 cur_height *= depth_to_space_params->block_size;
 cur_width *= depth_to_space_params->block_size;
 break;
+case MIRROR_PAD:
+pad_params = (LayerPadParams *)network->layers[layer].params;
+cur_height = cur_height + pad_params->paddings[1][0] + 
pad_params->paddings[1][1];
+cur_width = cur_width + pad_params->paddings[2][0] + 
pad_params->paddings[2][1];
+cur_channels = cur_channels + pad_params->paddings[3][0] + 
pad_params->paddings[3][1];
+break;
 default:
 return DNN_ERROR;
 }
@@ -110,6 +118,7 @@ DNNModel *ff_dnn_load_model_native(const char 
*model_filename)
 DNNLayerType layer_type;
 ConvolutionalParams *conv_params;
 DepthToSpaceParams *depth_to_space_params;
+LayerPadParams *pad_params;
 
 model = av_malloc(sizeof(DNNModel));
 if (!model){
@@ -207,6 +216,23 @@ DNNModel *ff_dnn_load_model_native(const char 
*model_filename)
 network->layers[layer].type = DEPTH_TO_SPACE;
 network->layers[layer].params = depth_to_space_params;
 break;
+case MIRROR_PAD:
+pad_params = av_malloc(sizeof(LayerPadParams));
+if (!pad_params){
+avio_closep(_file_context);
+ff_dnn_free_model_native();
+return NULL;
+}
+pad_params->mode = (int32_t)avio_rl32(model_file_context);
+dnn_size += 4;
+for (i = 0; i < 4; ++i) {
+pad_params->paddings[i][0] = avio_rl32(model_file_context);
+pad_params->paddings[i][1] = avio_rl32(model_file_context);
+dnn_size += 8;
+}
+network->layers[layer].type = MIRROR_PAD;
+network->layers[layer].params = pad_params;
+break;
 default:
 avio_closep(_file_context);
 ff_dnn_free_model_native();
@@ -314,6 +340,7 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel 
*model, DNNData *output
 InputParams *input_params;
 ConvolutionalParams *conv_params;
 DepthToSpaceParams *depth_to_space_params;
+LayerPadParams *pad_params;
 
 if (network->layers_num <= 0 || network->layers[0].type != INPUT || 
!network->layers[0].output){
 return DNN_ERROR;
@@ -348,6 +375,14 @@ DNNReturnType ff_dnn_execute_model_native(const DNNModel 
*model, DNNData *output
 cur_width *= depth_to_space_params->block_size;
 cur_channels /= depth_to_space_params->block_size * 
depth_to_space_params->block_size;
 break;
+case MIRROR_PAD:
+pad_params = (LayerPadParams *)network->layers[layer].params;
+dnn_execute_layer_pad(network->layers[layer - 1].output, 
network->layers[layer].output,
+  pad_params, 1, cur_height, cur_width, 
cur_channels);
+cur_height = cur_height + pad_params->paddings[1][0] + 
pad_params->paddings[1][1];
+cur_width = cur_width + pad_params->paddings[2][0] + 
pad_params->paddings[2][1];
+cur_channels = cur_channels + pad_params->paddings[3][0] + 
pad_params->paddings[3][1];
+break;
 case INPUT:
 return DNN_ERROR;
 }
diff --git a/libavfilter/dnn/dnn_backend_native.h 
b/libavfilter/dnn/dnn_backend_native.h
index 8ef1855..b6f9533 100644
--- a/libavfilter/dnn/dnn_backend_native.h
+++ b/libavfilter/dnn/dnn_backend_native.h
@@ -30,7 +30,7 @@
 #include "../dnn_interface.h"
 #include "libavformat/avio.h"
 
-typedef enum {INPUT, CONV, DEPTH_TO_SPACE} DNNLayerType;
+typedef enum {INPUT, CONV, DEPTH_TO_SPACE, MIRROR_PAD}