add test case

Author: RandyShuai

tests/backend_test_base.py

@@ -87,6 +87,7 @@ def run_test_case(self, feed_dict, input_names_with_port, output_names_with_port
         graph_def = None
         if convert_var_to_const:
             with tf.Session() as sess:
+                tf.tables_initializer().run()
                 variables_lib.global_variables_initializer().run()
                 output_name_without_port = [n.split(':')[0] for n in output_names_with_port]
                 graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def,
@@ -96,6 +97,7 @@ def run_test_case(self, feed_dict, input_names_with_port, output_names_with_port
             tf.import_graph_def(graph_def, name='')
 
         with tf.Session() as sess:
+            tf.tables_initializer().run()
             variables_lib.global_variables_initializer().run()
             output_dict = []
             for out_name in output_names_with_port:

tests/test_backend.py

@@ -10,9 +10,11 @@
 import unittest
 from itertools import product
 
+import os
 import numpy as np
 import tensorflow as tf
 
+from tensorflow.python.ops import lookup_ops
 from backend_test_base import Tf2OnnxBackendTestBase
 # pylint reports unused-wildcard-import which is false positive, __all__ is defined in common
 from common import *  # pylint: disable=wildcard-import,unused-wildcard-import
@@ -109,7 +111,7 @@ def _run_test_case(self, output_names_with_port, feed_dict, **kwargs):
         kwargs["convert_var_to_const"] = False
         kwargs["constant_fold"] = False
         return self.run_test_case(feed_dict, [], output_names_with_port, **kwargs)
-
+    '''
     def _test_expand_dims_known_rank(self, idx):
         tf.reset_default_graph()
         x_val = make_xval([3, 4])
@@ -2973,7 +2975,20 @@ def test_Conv2DBackpropInput_valid(self):
         _ = tf.nn.conv2d_backprop_input(input_sizes, filters, out_backprop, strides=[1, 1, 1, 1], padding='VALID',
                                         name=_TFOUTPUT)
         self._run_test_case([_OUTPUT], {_INPUT: input_sizes_val, _INPUT1: filters_val, _INPUT2: out_backprop_val})
-
+    '''
+    @check_opset_min_version(1, "CategoryMapper")
+    def test_hashtable_lookup(self):
+        filnm = "vocab.tmp"
+        words = ["apple","pear","banana","cherry","grape"]
+        query = np.array(['cherry'],dtype=object)
+        with open(filnm, "w") as f:
+            for word in words:
+                f.write(word + "\n")
+        query_holder = tf.placeholder(tf.string, shape=[len(query)], name=_TFINPUT)
+        hash_table = lookup_ops.index_table_from_file(filnm)
+        lookup_results = hash_table.lookup(query_holder)
+        self._run_test_case([lookup_results.name], {_INPUT: query})
+        os.remove(filnm) 
 
 if __name__ == '__main__':
     unittest_main()

tf2onnx/custom_opsets/onnx_ml.py

@@ -10,15 +10,15 @@
 @tf_op("HashTableV2")
 class HashTable:
     @classmethod
-    def version_11(cls, ctx, node, **kwargs):
+    def version_1(cls, ctx, node, **kwargs):
         """ HashTable will be removed """
         pass
 
 
 @tf_op("LookupTableFindV2")
 class LookupTableFind:
     @classmethod
-    def version_11(cls, ctx, node, **kwargs):
+    def version_1(cls, ctx, node, **kwargs):
         """ convert lookup to category mapper """
         table_node = node.inputs[0]
         file_path = table_node.get_attr_value("shared_name")[11:-6]
@@ -28,12 +28,14 @@ def version_11(cls, ctx, node, **kwargs):
             for i, s in enumerate(f.readlines()):
                 cats_int64s.append(i)
                 cats_strings.append(s.strip())
+        node_name = node.name
         node_inputs = node.input
         node_outputs = node.output
         ctx.remove_node(node.name)
-        ctx.make_node("CategoryMapper", domain=constants.AI_ONNX_ML_DOMAIN,
-                      inputs=node_inputs[1: 2], outputs=node_outputs,
-                      attr={'cats_int64s': cats_int64s, 'cats_strings': cats_strings})
+        new_node = ctx.make_node("CategoryMapper", domain=constants.AI_ONNX_ML_DOMAIN,
+                                 name=node_name, inputs=node_inputs[1: 2], outputs=node_outputs,
+                                 attr={'cats_int64s': cats_int64s, 'cats_strings': cats_strings})
+        ctx.set_shape(new_node.name + ":0", [-1])
         customer_nodes = ctx.find_output_consumers(table_node.output[0])
         if len(customer_nodes) == 0:
             ctx.remove_node(table_node.name)

tf2onnx/onnx_opset/controlflow.py

@@ -369,13 +369,13 @@ def version_9(cls, ctx, node, **kwargs):
 @tf_op("IteratorV2")
 class Iterator:
     @classmethod
-    def version_11(cls, ctx, node, **kwargs):
+    def version_1(cls, ctx, node, **kwargs):
         ctx.remove_node(node.name)
 
 @tf_op("IteratorGetNext")
 class IteratorGetNext:
     @classmethod
-    def version_11(cls, ctx, node, **kwargs):
+    def version_1(cls, ctx, node, **kwargs):
         output_names = node.output
         ctx.remove_node(node.name)
         output_types = list(node.get_attr('output_types').ints)