1 files changed, 176 insertions, 0 deletions
diff --git a/inference-engine/thirdparty/clDNN/src/include/convolution_inst.h b/inference-engine/thirdparty/clDNN/src/include/convolution_inst.h
new file mode 100644
index 000000000..c4a175b1e
--- /dev/null
+++ b/inference-engine/thirdparty/clDNN/src/include/convolution_inst.h
@@ -0,0 +1,176 @@
+/*
+// Copyright (c) 2016 Intel Corporation
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//      http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+*/
+
+///////////////////////////////////////////////////////////////////////////////////////////////////
+#pragma once
+#include "api/CPP/convolution.hpp"
+#include "primitive_inst.h"
+
+#include <memory>
+
+namespace cldnn
+{
+
+template <>
+struct typed_program_node<convolution> : public typed_program_node_base<convolution>
+{
+    using parent = typed_program_node_base<convolution>;
+
+public:
+    typed_program_node(std::shared_ptr<primitive> prim, program_impl& prog)
+        : parent(prim, prog)
+        , split(this->get_primitive()->split())
+        , depthwise_sep_opt(false)
+        , transposed(false)
+        , input_qf(this->get_primitive()->input_quantization_factor)
+        , output_qf(this->get_primitive()->output_quantization_factor)
+    {
+    }
+
+    void set_split(int32_t node_split) { split = node_split; }
+    int32_t get_split() const { return split; }
+
+    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_transposed(bool node_transposed) { transposed = node_transposed; }
+    bool get_transposed() const { return transposed; }
+
+    decltype(auto) input() const { return get_dependency(0); }
+
+    decltype(auto) weights(size_t idx = 0) const
+    {
+        if (static_cast<int32_t>(idx) >= this->get_split())
+            throw std::range_error("weights offset too big");
+
+        return get_dependency(1 + idx);
+    }
+
+    decltype(auto) bias(size_t idx = 0) const
+    { 
+        if (static_cast<int32_t>(idx) >= this->get_split())
+            throw std::range_error("bias offset too big");
+
+        return get_dependency(1 + this->get_split() + idx);
+    }
+
+    decltype(auto) weights_quantization_factors(size_t idx = 0) const
+    {
+        if (static_cast<int32_t>(idx) >= this->get_split())
+            throw std::range_error("quantization factor offset too big");
+
+        return get_dependency(1 + 2*this->get_split() + idx);
+    }
+
+    decltype(auto) output_calibration_factors(size_t idx = 0) const
+    {
+        if (static_cast<int32_t>(idx) >= this->get_split())
+            throw std::range_error("calibration factor offset too big");
+
+        return get_dependency(1 + 3 * this->get_split() + idx);
+    }
+
+    bool bias_term() const
+    {
+        return get_primitive()->bias.size() > 0;
+    }
+
+    bool weights_quantization_term() const
+    {
+        return get_primitive()->weights_quantization_factors.size() > 0;
+    }
+
+    bool output_calibration_term() const
+    {
+        return get_primitive()->output_calibration_factors.size() > 0;
+    }
+    
+    float get_input_qf() const { return input_qf; }
+    float get_output_qf() const { return output_qf; }
+
+private:
+    int32_t split;
+    bool depthwise_sep_opt;
+    bool transposed;
+    float input_qf;
+    float output_qf;
+};
+
+using convolution_node = typed_program_node<convolution>;
+
+template <>
+class typed_primitive_inst<convolution> : public typed_primitive_inst_base<convolution>
+{
+    using parent = typed_primitive_inst_base<convolution>;
+
+public:
+    static layout calc_output_layout(convolution_node const& node);
+    static std::string to_string(convolution_node const& node);
+
+public:
+    typed_primitive_inst(network_impl& network, convolution_node const& node);
+
+    decltype(auto)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);
+    }
+
+    decltype(auto) bias_memory(size_t index) const
+    { 
+        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);
+    }
+
+    decltype(auto) weights_quantization_factors_memory(size_t index) const
+    {
+        if (static_cast<int32_t>(index) >= node.get_split())
+            throw std::range_error("quantization factors offset too big");
+
+        return dep_memory(1 + 2*node.get_split() + index);
+    }
+
+    decltype(auto) output_calibration_factors_memory(size_t index) const
+    {
+        if (static_cast<int32_t>(index) >= node.get_split())
+            throw std::range_error("quantization factors offset too big");
+
+        return dep_memory(1 + 3 * node.get_split() + index);
+    }
+
+    bool bias_term() const
+    {
+        return node.bias_term();
+    }
+
+    bool weights_quantization_factors_term() const
+    {
+        return node.weights_quantization_term();
+    }
+
+    bool output_calibration_factors_term() const
+    {
+        return node.output_calibration_term();
+    }
+};
+
+using convolution_inst = typed_primitive_inst<convolution>;
+
+}