modifications to operators

src/tf/tf.cpp

@@ -177,13 +177,13 @@ struct tf_parser
         add_mem_op("GatherV2", &tf_parser::parse_gather, false);
         add_mem_op("MatMul", &tf_parser::parse_matmul, false);
         add_mem_op("MaxPool", &tf_parser::parse_pooling);
-        add_mem_op("Mean", &tf_parser::parse_mean);
+        add_mem_op("Mean", &tf_parser::parse_mean, false);
         add_mem_op("OneHot", &tf_parser::parse_onehot, false);
         add_mem_op("Pack", &tf_parser::parse_pack, false);
         add_mem_op("Pad", &tf_parser::parse_pad);
         add_mem_op("Reshape", &tf_parser::parse_reshape, false);
         add_mem_op("Slice", &tf_parser::parse_slice, false);
-        add_mem_op("Softmax", &tf_parser::parse_softmax);
+        add_mem_op("Softmax", &tf_parser::parse_softmax<op::softmax>, false);
         add_mem_op("Squeeze", &tf_parser::parse_squeeze, false);
         add_mem_op("StridedSlice", &tf_parser::parse_stridedslice, false);
         add_mem_op("Transpose", &tf_parser::parse_transpose, false);
@@ -548,7 +548,7 @@ struct tf_parser
         }
         if(contains(attributes, "transpose_b"))
         {
-            transb = attributes.at("transpose_a").b();
+            transb = attributes.at("transpose_b").b();
         }
 
         if(contains(attributes, "adj_x"))
@@ -575,23 +575,24 @@ struct tf_parser
     parse_mean(const std::string&, attribute_map attributes, std::vector<instruction_ref> args)
     {
         bool keep_dims = attributes.at("keep_dims").b();
-        std::vector<int32_t> hw_axes{2, 3};
+        // 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"};
-            op.lengths[0] = lens[2];
-            op.lengths[1] = lens[3];
-            auto l0       = prog.add_instruction(op, args.front());
-            if(keep_dims)
-                return l0;
-            return prog.add_instruction(
-                op::squeeze{std::vector<int64_t>(hw_axes.begin(), hw_axes.end())}, l0);
-        }
-        MIGRAPHX_THROW("MIGraphX does not support mean outside of GlobalAvgPool transformation");
+        auto axes = args[1]->eval().get<int32_t>().to_vector();
+        std::vector<int64_t> axes_int64 = std::vector<int64_t>(axes.begin(), axes.end());
+
+        // if(axes == hw_axes and lens.size() == 4)
+        // {
+        // op::pooling op{"average"};
+        // op.lengths[0] = lens[2];
+        // op.lengths[1] = lens[3];
+        auto l0       = prog.add_instruction(op::reduce_mean{axes_int64}, args.front());
+        if(keep_dims)
+            return l0;
+        return prog.add_instruction(
+            op::squeeze{axes_int64}, l0);
+        // }
+        // MIGRAPHX_THROW("MIGraphX does not support mean outside of GlobalAvgPool transformation");
     }
 
     instruction_ref
@@ -763,14 +764,24 @@ struct tf_parser
         }
     }
 
-    instruction_ref
-    parse_softmax(const std::string&, const attribute_map&, std::vector<instruction_ref> args)
+    // template to facilitate the logsoftmax later
+    template <class Op>
+    instruction_ref parse_softmax(const std::string&,
+                                  const attribute_map& attributes,
+                                  std::vector<instruction_ref> args)
     {
-        auto dims = args.front()->get_shape().lens();
-        auto r =
-            prog.add_instruction(op::reshape{{long(dims[0]), long(dims[1]), 1, 1}}, args.front());
-        auto s = prog.add_instruction(op::softmax{}, r);
-        return prog.add_instruction(op::reshape{{long(dims[0]), long(dims[1])}}, s);
+        int axis = -1;
+        auto num_dims = args[0]->get_shape().lens().size();
+        if(contains(attributes, "axis"))
+        {
+            axis = static_cast<int>(attributes.at("axis").i());
+        }
+        if(axis < 0)
+        {
+            axis += num_dims;
+        }
+
+        return prog.add_instruction(Op{axis}, make_contiguous(args[0]));
     }
 
     instruction_ref parse_squeeze(const std::string&,