libavfilter: Adds on the fly generation of default DNN models for tensorflow backend instead of storing binary model.

Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
author: Sergey Lavrushkin <dualfal@gmail.com> 2018-07-27 19:31:55 +0300
committer: Pedro Arthur <bygrandao@gmail.com> 2018-08-07 11:58:03 -0300
commit: 4eb63efbdaea6d36ad94f1bb0dd129b7f7aaa899 (patch)
tree: c33879607c8c16eacd64a1313c1b3a4a0946150d /libavfilter/dnn_backend_tf.c
parent: 243ecadad5e5e83afdd518c067030e12ac457120 (diff)
download: ffmpeg-4eb63efbdaea6d36ad94f1bb0dd129b7f7aaa899.tar.gz
1 files changed, 231 insertions, 40 deletions
diff --git a/libavfilter/dnn_backend_tf.c b/libavfilter/dnn_backend_tf.c
index 302ff9e4e1..51608c73d9 100644
--- a/libavfilter/dnn_backend_tf.c
+++ b/libavfilter/dnn_backend_tf.c
@@ -203,52 +203,191 @@ DNNModel* ff_dnn_load_model_tf(const char* model_filename)
     return model;
 }
 
-DNNModel* ff_dnn_load_default_model_tf(DNNDefaultModel model_type)
+static TF_Operation* add_pad_op(TFModel* tf_model, TF_Operation* input_op, int32_t pad)
 {
-    DNNModel* model = NULL;
-    TFModel* tf_model = NULL;
-    TF_Buffer* graph_def;
-    unsigned char* graph_data = NULL;
-    TF_ImportGraphDefOptions* graph_opts;
+    TF_OperationDescription* op_desc;
+    TF_Operation* op;
+    TF_Tensor* tensor;
+    TF_Output input;
+    int32_t* pads;
+    int64_t pads_shape[] = {4, 2};
+
+    op_desc = TF_NewOperation(tf_model->graph, "Const", "pads");
+    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;
+    TF_SetAttrTensor(op_desc, "value", tensor, tf_model->status);
+    if (TF_GetCode(tf_model->status) != TF_OK){
+        return NULL;
+    }
+    op = TF_FinishOperation(op_desc, tf_model->status);
+    if (TF_GetCode(tf_model->status) != TF_OK){
+        return NULL;
+    }
 
-    graph_def = TF_NewBuffer();
-    switch (model_type){
-    case DNN_SRCNN:
-        graph_data = av_malloc(srcnn_tf_size);
-        if (!graph_data){
-            TF_DeleteBuffer(graph_def);
+    op_desc = TF_NewOperation(tf_model->graph, "MirrorPad", "mirror_pad");
+    input.oper = input_op;
+    input.index = 0;
+    TF_AddInput(op_desc, input);
+    input.oper = op;
+    TF_AddInput(op_desc, input);
+    TF_SetAttrType(op_desc, "T", TF_FLOAT);
+    TF_SetAttrType(op_desc, "Tpaddings", TF_INT32);
+    TF_SetAttrString(op_desc, "mode", "SYMMETRIC", 9);
+    op = TF_FinishOperation(op_desc, tf_model->status);
+    if (TF_GetCode(tf_model->status) != TF_OK){
+        return NULL;
+    }
+
+    return op;
+}
+
+static TF_Operation* add_const_op(TFModel* tf_model, const float* values, const int64_t* dims, int dims_len, const char* name)
+{
+    int dim;
+    TF_OperationDescription* op_desc;
+    TF_Tensor* tensor;
+    size_t len;
+
+    op_desc = TF_NewOperation(tf_model->graph, "Const", name);
+    TF_SetAttrType(op_desc, "dtype", TF_FLOAT);
+    len = sizeof(float);
+    for (dim = 0; dim < dims_len; ++dim){
+        len *= dims[dim];
+    }
+    tensor = TF_AllocateTensor(TF_FLOAT, dims, dims_len, len);
+    memcpy(TF_TensorData(tensor), values, len);
+    TF_SetAttrTensor(op_desc, "value", tensor, tf_model->status);
+    if (TF_GetCode(tf_model->status) != TF_OK){
+        return NULL;
+    }
+
+    return TF_FinishOperation(op_desc, tf_model->status);
+}
+
+static TF_Operation* add_conv_layers(TFModel* tf_model, const float** consts, const int64_t** consts_dims,
+                                     const int* consts_dims_len, const char** activations,
+                                     TF_Operation* input_op, int layers_num)
+{
+    int i;
+    TF_OperationDescription* op_desc;
+    TF_Operation* op;
+    TF_Operation* transpose_op;
+    TF_Output input;
+    int64_t strides[] = {1, 1, 1, 1};
+    int32_t* transpose_perm;
+    TF_Tensor* tensor;
+    int64_t transpose_perm_shape[] = {4};
+    #define NAME_BUFF_SIZE 256
+    char name_buffer[NAME_BUFF_SIZE];
+
+    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));
+    transpose_perm = (int32_t*)TF_TensorData(tensor);
+    transpose_perm[0] = 1;
+    transpose_perm[1] = 2;
+    transpose_perm[2] = 3;
+    transpose_perm[3] = 0;
+    TF_SetAttrTensor(op_desc, "value", tensor, tf_model->status);
+    if (TF_GetCode(tf_model->status) != TF_OK){
+        return NULL;
+    }
+    transpose_op = TF_FinishOperation(op_desc, tf_model->status);
+    if (TF_GetCode(tf_model->status) != TF_OK){
+        return NULL;
+    }
+
+    input.index = 0;
+    for (i = 0; i < layers_num; ++i){
+        snprintf(name_buffer, NAME_BUFF_SIZE, "conv_kernel%d", i);
+        op = add_const_op(tf_model, consts[i << 1], consts_dims[i << 1], consts_dims_len[i << 1], name_buffer);
+        if (TF_GetCode(tf_model->status) != TF_OK || op == NULL){
             return NULL;
         }
-        memcpy(graph_data, srcnn_tf_model, srcnn_tf_size);
-        graph_def->data = (void*)graph_data;
-        graph_def->length = srcnn_tf_size;
-        graph_def->data_deallocator = free_buffer;
-        break;
-    case DNN_ESPCN:
-        graph_data = av_malloc(espcn_tf_size);
-        if (!graph_data){
-            TF_DeleteBuffer(graph_def);
+
+        snprintf(name_buffer, NAME_BUFF_SIZE, "transpose%d", i);
+        op_desc = TF_NewOperation(tf_model->graph, "Transpose", name_buffer);
+        input.oper = op;
+        TF_AddInput(op_desc, input);
+        input.oper = transpose_op;
+        TF_AddInput(op_desc, input);
+        TF_SetAttrType(op_desc, "T", TF_FLOAT);
+        TF_SetAttrType(op_desc, "Tperm", TF_INT32);
+        op = TF_FinishOperation(op_desc, tf_model->status);
+        if (TF_GetCode(tf_model->status) != TF_OK){
+            return NULL;
+        }
+
+        snprintf(name_buffer, NAME_BUFF_SIZE, "conv2d%d", i);
+        op_desc = TF_NewOperation(tf_model->graph, "Conv2D", name_buffer);
+        input.oper = input_op;
+        TF_AddInput(op_desc, input);
+        input.oper = op;
+        TF_AddInput(op_desc, input);
+        TF_SetAttrType(op_desc, "T", TF_FLOAT);
+        TF_SetAttrIntList(op_desc, "strides", strides, 4);
+        TF_SetAttrString(op_desc, "padding", "VALID", 5);
+        input_op = TF_FinishOperation(op_desc, tf_model->status);
+        if (TF_GetCode(tf_model->status) != TF_OK){
+            return NULL;
+        }
+
+        snprintf(name_buffer, NAME_BUFF_SIZE, "conv_biases%d", i);
+        op = add_const_op(tf_model, consts[(i << 1) + 1], consts_dims[(i << 1) + 1], consts_dims_len[(i << 1) + 1], name_buffer);
+        if (TF_GetCode(tf_model->status) != TF_OK || op == NULL){
+            return NULL;
+        }
+
+        snprintf(name_buffer, NAME_BUFF_SIZE, "bias_add%d", i);
+        op_desc = TF_NewOperation(tf_model->graph, "BiasAdd", name_buffer);
+        input.oper = input_op;
+        TF_AddInput(op_desc, input);
+        input.oper = op;
+        TF_AddInput(op_desc, input);
+        TF_SetAttrType(op_desc, "T", TF_FLOAT);
+        input_op = TF_FinishOperation(op_desc, tf_model->status);
+        if (TF_GetCode(tf_model->status) != TF_OK){
+            return NULL;
+        }
+
+        snprintf(name_buffer, NAME_BUFF_SIZE, "activation%d", i);
+        op_desc = TF_NewOperation(tf_model->graph, activations[i], name_buffer);
+        input.oper = input_op;
+        TF_AddInput(op_desc, input);
+        TF_SetAttrType(op_desc, "T", TF_FLOAT);
+        input_op = TF_FinishOperation(op_desc, tf_model->status);
+        if (TF_GetCode(tf_model->status) != TF_OK){
             return NULL;
         }
-        memcpy(graph_data, espcn_tf_model, espcn_tf_size);
-        graph_def->data = (void*)graph_data;
-        graph_def->length = espcn_tf_size;
-        graph_def->data_deallocator = free_buffer;
-        break;
-    default:
-        TF_DeleteBuffer(graph_def);
-        return NULL;
     }
 
+    return input_op;
+}
+
+DNNModel* ff_dnn_load_default_model_tf(DNNDefaultModel model_type)
+{
+    DNNModel* model = NULL;
+    TFModel* tf_model = NULL;
+    TF_OperationDescription* op_desc;
+    TF_Operation* op;
+    TF_Operation* const_ops_buffer[6];
+    TF_Output input;
+    int64_t input_shape[] = {1, -1, -1, 1};
+
+    input.index = 0;
+
     model = av_malloc(sizeof(DNNModel));
     if (!model){
-        TF_DeleteBuffer(graph_def);
         return NULL;
     }
 
     tf_model = av_malloc(sizeof(TFModel));
     if (!tf_model){
-        TF_DeleteBuffer(graph_def);
         av_freep(&model);
         return NULL;
     }
@@ -258,16 +397,68 @@ DNNModel* ff_dnn_load_default_model_tf(DNNDefaultModel model_type)
 
     tf_model->graph = TF_NewGraph();
     tf_model->status = TF_NewStatus();
-    graph_opts = TF_NewImportGraphDefOptions();
-    TF_GraphImportGraphDef(tf_model->graph, graph_def, graph_opts, tf_model->status);
-    TF_DeleteImportGraphDefOptions(graph_opts);
-    TF_DeleteBuffer(graph_def);
+
+    #define CLEANUP_ON_ERROR(tf_model, model) { \
+        TF_DeleteGraph(tf_model->graph); \
+        TF_DeleteStatus(tf_model->status); \
+        av_freep(&tf_model); \
+        av_freep(&model); \
+        return NULL; \
+    }
+
+    op_desc = TF_NewOperation(tf_model->graph, "Placeholder", "x");
+    TF_SetAttrType(op_desc, "dtype", TF_FLOAT);
+    TF_SetAttrShape(op_desc, "shape", input_shape, 4);
+    op = TF_FinishOperation(op_desc, tf_model->status);
     if (TF_GetCode(tf_model->status) != TF_OK){
-        TF_DeleteGraph(tf_model->graph);
-        TF_DeleteStatus(tf_model->status);
-        av_freep(&tf_model);
-        av_freep(&model);
-        return NULL;
+        CLEANUP_ON_ERROR(tf_model, model);
+    }
+
+    switch (model_type){
+    case DNN_SRCNN:
+        op = add_pad_op(tf_model, op, 6);
+        if (!op){
+            CLEANUP_ON_ERROR(tf_model, model);
+        }
+        op = add_conv_layers(tf_model, srcnn_consts,
+                             srcnn_consts_dims, srcnn_consts_dims_len,
+                             srcnn_activations, op, 3);
+        if (!op){
+            CLEANUP_ON_ERROR(tf_model, model);
+        }
+        break;
+    case DNN_ESPCN:
+        op = add_pad_op(tf_model, op, 4);
+        if (!op){
+            CLEANUP_ON_ERROR(tf_model, model);
+        }
+        op = add_conv_layers(tf_model, espcn_consts,
+                             espcn_consts_dims, espcn_consts_dims_len,
+                             espcn_activations, op, 3);
+        if (!op){
+            CLEANUP_ON_ERROR(tf_model, model);
+        }
+
+        op_desc = TF_NewOperation(tf_model->graph, "DepthToSpace", "depth_to_space");
+        input.oper = op;
+        TF_AddInput(op_desc, input);
+        TF_SetAttrType(op_desc, "T", TF_FLOAT);
+        TF_SetAttrInt(op_desc, "block_size", 2);
+        op = TF_FinishOperation(op_desc, tf_model->status);
+        if (TF_GetCode(tf_model->status) != TF_OK){
+            CLEANUP_ON_ERROR(tf_model, model);
+        }
+        break;
+    default:
+        CLEANUP_ON_ERROR(tf_model, model);
+    }
+
+    op_desc = TF_NewOperation(tf_model->graph, "Identity", "y");
+    input.oper = op;
+    TF_AddInput(op_desc, input);
+    TF_FinishOperation(op_desc, tf_model->status);
+    if (TF_GetCode(tf_model->status) != TF_OK){
+        CLEANUP_ON_ERROR(tf_model, model);
     }
 
     model->model = (void*)tf_model;
author	Sergey Lavrushkin <dualfal@gmail.com>	2018-07-27 19:31:55 +0300
committer	Pedro Arthur <bygrandao@gmail.com>	2018-08-07 11:58:03 -0300
commit	4eb63efbdaea6d36ad94f1bb0dd129b7f7aaa899 (patch)
tree	c33879607c8c16eacd64a1313c1b3a4a0946150d /libavfilter/dnn_backend_tf.c
parent	243ecadad5e5e83afdd518c067030e12ac457120 (diff)
download	ffmpeg-4eb63efbdaea6d36ad94f1bb0dd129b7f7aaa899.tar.gz