add expanddims plus tests

src/tf/tf.cpp

@@ -37,7 +37,7 @@ struct tf_parser
 
     std::unordered_map<std::string, op_func> ops;
 
-    std::vector<size_t> parse_axes(const attribute_map& attributes, const std::string& s) const
+    std::vector<size_t> parse_axes(const attribute_map& attributes, const std::string& s, const size_t& num_dims) const
     {
         auto attrs = attributes.at(s).list().i();
         std::vector<size_t> axes;
@@ -45,14 +45,14 @@ struct tf_parser
         if(is_nhwc)
         {
             std::transform(axes.begin(), axes.end(), axes.begin(), [&](size_t axis) {
-                return parse_axis(axis);
+                return parse_axis(axis, num_dims);
             });
         }
         return axes;
     }
 
     template <class T>
-    std::vector<T> parse_axes(std::vector<T> axes) const
+    std::vector<T> parse_axes(std::vector<T> axes, const size_t& num_dims) const
     {
         if(is_nhwc)
         {
@@ -60,7 +60,7 @@ struct tf_parser
             std::transform(axes.begin(),
                            axes.end(),
                            std::back_inserter(new_axes),
-                           [&](size_t axis) { return parse_axis(axis); });
+                           [&](size_t axis) { return parse_axis(axis, num_dims); });
             return new_axes;
         }
         return axes;
@@ -75,17 +75,17 @@ struct tf_parser
         std::vector<T> new_data(prev_data.size());
         for(size_t i = 0; i < new_data.size(); i++)
         {
-            auto new_idx         = parse_axis(i);
+            auto new_idx         = parse_axis(i, new_data.size());
             new_data.at(new_idx) = prev_data.at(i);
         }
         prev_data = new_data;
     }
 
     template <class T>
-    T parse_axis(const T& dim) const
+    T parse_axis(const T& dim, const size_t& num_dims) const
     {
         T new_dim = dim;
-        if(is_nhwc)
+        if(is_nhwc and num_dims >= 4)
         {
             switch(dim)
             {
@@ -121,6 +121,7 @@ struct tf_parser
         add_mem_op("Const", &tf_parser::parse_constant);
         add_mem_op("Conv2D", &tf_parser::parse_conv);
         add_mem_op("DepthwiseConv2dNative", &tf_parser::parse_depthwiseconv);
+        add_mem_op("ExpandDims", &tf_parser::parse_expanddims);
         add_mem_op("FusedBatchNorm", &tf_parser::parse_batchnorm);
         add_mem_op("MatMul", &tf_parser::parse_matmul);
         add_mem_op("MaxPool", &tf_parser::parse_pooling);
@@ -251,7 +252,7 @@ struct tf_parser
     {
         // get index for axis within args
         size_t axis_idx = attributes.at("N").i();
-        size_t axis     = parse_axis(args[axis_idx]->eval().at<int64_t>());
+        size_t axis     = parse_axis(args[axis_idx]->eval().at<int64_t>(), args[0]->get_shape().lens().size());
         op::concat op{axis};
         // return only first N arguments (assuming last index is the axis value)
         return prog.add_instruction(
@@ -470,6 +471,24 @@ struct tf_parser
         return prog.add_instruction(op, {l0, new_weights});
     }
 
+    instruction_ref parse_expanddims(const std::string&, const attribute_map&, std::vector<instruction_ref> args)
+    {
+        std::vector<size_t> input_dims = args[0]->get_shape().lens();
+        std::vector<int64_t> new_dims(input_dims.begin(), input_dims.end()); 
+        size_t num_dims = input_dims.size();
+        int32_t dim = parse_axis(args[1]->eval().at<int32_t>(), num_dims);
+        
+        if (dim < 0)
+        {
+            new_dims.insert(new_dims.begin() + (num_dims + dim + 1), 1);
+        }
+        else
+        {
+            new_dims.insert(new_dims.begin() + dim, 1);
+        }
+        return prog.add_instruction(op::reshape{new_dims}, args[0]);
+    }
+
     instruction_ref
     parse_matmul(const std::string&, attribute_map attributes, std::vector<instruction_ref> args)
     {
@@ -499,11 +518,12 @@ struct tf_parser
     instruction_ref
     parse_mean(const std::string&, attribute_map attributes, std::vector<instruction_ref> args)
     {
-        auto axes      = parse_axes(args[1]->eval().get<int32_t>().to_vector());
         bool keep_dims = attributes.at("keep_dims").b();
         std::vector<int32_t> hw_axes{2, 3};
         // check if conditions for GlobalAvgPool are met
         auto lens = args[0]->get_shape().lens();
+        auto axes = parse_axes(args[1]->eval().get<int32_t>().to_vector(), lens.size());
+
         if(axes == hw_axes and lens.size() == 4)
         {
             op::pooling op{"average"};
@@ -534,8 +554,7 @@ struct tf_parser
                            " must be smaller than input size " + to_string(input_size));
         }
         // check if input arg needs axis to be converted to NCHW
-        if(input_size >= 4)
-            axis = parse_axis(axis);
+        axis = parse_axis(axis, input_size);
 
         std::transform(
             args.begin(),
@@ -676,14 +695,15 @@ struct tf_parser
                                   std::vector<instruction_ref> args)
     {
         op::squeeze op;
-        auto axes = parse_axes(attributes, "squeeze_dims");
+        auto input_dims = args[0]->get_shape().lens();
+        auto axes = parse_axes(attributes, "squeeze_dims", input_dims.size());
         copy(axes, std::back_inserter(op.axes));
-        auto args0_dims = args[0]->get_shape().lens();
+
         if(op.axes.empty()) // no squeeze_dims provided, remove any dim that equals 1
         {
-            for(size_t i = 0; i < args0_dims.size(); i++)
+            for(size_t i = 0; i < input_dims.size(); i++)
             {
-                if(args0_dims.at(i) == 1)
+                if(input_dims.at(i) == 1)
                 {
                     op.axes.push_back(i);
                 }
@@ -723,10 +743,7 @@ struct tf_parser
             if(((shrink_axis_mask >> i) & bitwise_compare) == 1)
                 squeeze_axes.push_back(i);
         }
-        if(num_axes >= 4)
-        {
-            squeeze_axes = parse_axes(squeeze_axes);
-        }
+        squeeze_axes = parse_axes(squeeze_axes, num_axes);
 
         auto l0 = prog.add_instruction(op, args[0]);
         return prog.add_instruction(op::squeeze{squeeze_axes}, l0);

test/tf/tf_test.cpp

@@ -146,6 +146,20 @@ TEST_CASE(depthwiseconv_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(expanddims_test)
+{
+    migraphx::program p;
+    
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2,3,4}});
+    p.add_literal(-1);
+    p.add_literal(0);
+    p.add_instruction(migraphx::op::reshape{{2,3,4,1}}, l0);
+    p.add_instruction(migraphx::op::reshape{{1,2,3,4}}, l0);
+    auto prog = migraphx::parse_tf("expanddims_test.pb", true);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(identity_test)
 {
     migraphx::program p;