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From GitBox <...@apache.org>
Subject [GitHub] [incubator-tvm] maheshambule commented on a change in pull request #5052: [TARGET] ONNX codegen
Date Thu, 11 Jun 2020 08:31:50 GMT

maheshambule commented on a change in pull request #5052:
URL: https://github.com/apache/incubator-tvm/pull/5052#discussion_r438627012



##########
File path: python/tvm/contrib/target/onnx.py
##########
@@ -0,0 +1,905 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you 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.
+# pylint: disable=invalid-name, import-self, len-as-condition, unused-argument, too-many-lines,
redefined-builtin
+"""Relay to ONNX codegen """
+
+import os
+import struct
+import copy
+import numpy
+import onnx
+import onnx.utils
+from onnx import numpy_helper, OperatorSetIdProto, defs
+import tvm
+from tvm import relay
+import tvm._ffi
+from tvm.relay.expr_functor import ExprVisitor
+from tvm.relay.ty import TupleType, TensorType
+
+ONNX_OPSET_VERSONS_SUPPORTED = [11]
+
+
+def tvm_array_to_list(arr):
+    return tuple(x.value for x in arr)
+
+
+def get_onnx_version():
+    return onnx.__version__
+
+
+def infer_type(node):
+    """A method to infer the type of a relay expression."""
+    mod = tvm.IRModule.from_expr(node)
+    mod = relay.transform.InferType()(mod)
+    entry = mod["main"]
+    return entry if isinstance(node, relay.Function) else entry.body
+
+
+def call_node_infer_type(node):
+    """infer the output types of call node"""
+    infer_out = infer_type(node)
+    out_type = infer_out._checked_type_
+    types = []
+    if isinstance(out_type, TensorType):
+        types.append(out_type)
+    elif isinstance(out_type, TupleType):
+        for tupe_type in out_type.fields:
+            types.append(tupe_type)

Review comment:
       changed.




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