Publishing 2019 R1 content

[platform/upstream/dldt.git] / inference-engine / thirdparty / clDNN / src / include / deconvolution_inst.h

diff --git a/inference-engine/thirdparty/clDNN/src/include/deconvolution_inst.h b/inference-engine/thirdparty/clDNN/src/include/deconvolution_inst.h
index a2e1516..adfe356 100644 (file)
--- a/inference-engine/thirdparty/clDNN/src/include/deconvolution_inst.h
+++ b/inference-engine/thirdparty/clDNN/src/include/deconvolution_inst.h
@@ -32,7 +32,9 @@ public:
         : parent(prim, prog)
         , split(this->get_primitive()->split())
         , depthwise_sep_opt(false)
+        , groups(this->get_primitive()->groups)
     {
+        support_padding(true);
     }
 
     
@@ -42,6 +44,9 @@ public:
     void set_depthwise_sep_opt(bool node_depthwise_sep_opt) { depthwise_sep_opt = node_depthwise_sep_opt; }
     bool get_depthwise_sep_opt() const { return depthwise_sep_opt; }
 
+    void set_groups(uint32_t node_groups) { groups = node_groups; }
+    uint32_t get_groups() const { return groups; }
+
     program_node& input() const { return get_dependency(0); }
 
     program_node& weights(size_t idx = 0) const
@@ -73,21 +78,22 @@ public:
         if (static_cast<int32_t>(idx) > 0)
             throw std::range_error("Only one input for fused sum is supported");
 
-        int d_idx = 1 + this->get_split() + idx;
+        size_t d_idx = 1 + this->get_split() + idx;
         d_idx += bias_term() ? this->get_split() : 0;
         return get_dependency(d_idx);
     }
 
     bool has_fused_sum() const
     {
-        int d_idx = 1 + this->get_split();
+        size_t d_idx = 1 + this->get_split();
         d_idx += bias_term() ? this->get_split() : 0;
-        return static_cast<int>(dependencies.size()) == (d_idx + 1);
+        return dependencies.size() == (d_idx + 1);
     }
 
 private:
     int32_t split;
     bool depthwise_sep_opt;
+    uint32_t groups;
 };
 
 using deconvolution_node = typed_program_node<deconvolution>;
@@ -106,21 +112,28 @@ public:
 
     memory_impl& weights_memory(size_t index) const
     {
-        if (static_cast<int32_t>(index) >= node.get_split())
-            throw std::range_error("weights offset too big");
-
-        return dep_memory(1 + index);
+        if (node.get_groups() == 1) {
+            if (static_cast<int32_t>(index) >= node.get_split())
+                throw std::range_error("weights offset too big");
+            return dep_memory(1 + index);
+        }
+        else { // all weights are in one buffer
+            return dep_memory(1);
+        }
     }
 
     memory_impl& bias_memory(size_t index) const
     {
-        if (argument.bias.size() == 0 && static_cast<int32_t>(index) >= node.get_split())
-            throw std::range_error("no bias data");
-
-        if (static_cast<int32_t>(index) > node.get_split())
-            throw std::range_error("bias offset too big");
-
-        return dep_memory(1 + node.get_split() + index);
+        if (node.get_groups() == 1) {
+            if (argument.bias.size() == 0 && static_cast<int32_t>(index) >= node.get_split())
+                throw std::range_error("no bias data");
+            if (static_cast<int32_t>(index) > node.get_split())
+                throw std::range_error("bias offset too big");
+            return dep_memory(1 + node.get_split() + index);
+        }
+        else { // all bias are in one buffer
+            return dep_memory(2);
+        }
     }
 
     bool bias_term() const