Tensorflow script upgrade from 1.13.1 to 2.0.0, so that it can run in both versionsw (#4963)

python/tvm/relay/frontend/tensorflow.py

@@ -1259,7 +1259,7 @@ def _broadcast(name):
     def _impl(inputs, attr, params):
         return AttrCvt(
             op_name=name,
-            ignores=['name', 'Tidx']
+            ignores=['name', 'incompatible_shape_error', 'Tidx']
         )(inputs, attr)
     return _impl
 

python/tvm/relay/frontend/tensorflow_parser.py

@@ -73,7 +73,7 @@ class TFParser(object):
     def _get_output_names(self):
         """Return the concatenated output names"""
         try:
-            import tensorflow as tf
+            import tensorflow.compat.v1 as tf
         except ImportError:
             raise ImportError(
                 "InputConfiguration: Unable to import tensorflow which is "

python/tvm/relay/testing/tf.py

@@ -219,9 +219,9 @@ def get_workload(model_path, model_sub_path=None):
 
     # Creates graph from saved graph_def.pb.
     with tf_compat_v1.gfile.FastGFile(path_model, 'rb') as f:
-        graph_def = tf.GraphDef()
+        graph_def = tf_compat_v1.GraphDef()
         graph_def.ParseFromString(f.read())
-        graph = tf.import_graph_def(graph_def, name='')
+        graph = tf_compat_v1.import_graph_def(graph_def, name='')
         return graph_def
 
 #######################################################################

tests/python/frontend/keras/test_forward.py

@@ -22,11 +22,16 @@ from tvm.contrib import graph_runtime
 from tvm.relay.testing.config import ctx_list
 import keras
 
-import tensorflow as tf
+try:
+    import tensorflow.compat.v1 as tf
+except ImportError:
+    import tensorflow as tf
+
 from tensorflow import keras as tf_keras
+from packaging import version as package_version
 # prevent Keras from using up all gpu memory
 if tf.executing_eagerly():
-    gpus = tf.config.list_physical_devices('GPU')
+    gpus = tf.config.experimental.list_physical_devices('GPU')
     for gpu in gpus:
         tf.config.experimental.set_memory_growth(gpu, True)
 else:
@@ -363,7 +368,7 @@ class TestKeras:
                     keras.layers.SimpleRNN(units=16, return_state=False,
                         activation='tanh'),
                     keras.layers.GRU(units=16, return_state=False,
-                        recurrent_activation='sigmoid', activation='tanh')]
+                        recurrent_activation='sigmoid', activation='tanh', reset_after=False)]
         for rnn_func in rnn_funcs:
             x = rnn_func(data)
             keras_model = keras.models.Model(data, x)

tests/python/frontend/tensorflow/test_control_flow.py

@@ -16,7 +16,11 @@
 # under the License.
 """Unit tests for converting TensorFlow control flow op to Relay."""
 import pytest
-import tensorflow as tf
+try:
+    import tensorflow.compat.v1 as tf
+    tf.disable_v2_behavior()
+except ImportError:
+    import tensorflow as tf
 import numpy as np
 from tvm import nd
 from tvm import relay

tests/python/frontend/tensorflow/test_debugging.py

@@ -15,7 +15,11 @@
 # specific language governing permissions and limitations
 # under the License.
 """Unit tests for converting TensorFlow debugging ops to Relay."""
-import tensorflow as tf
+try:
+    import tensorflow.compat.v1 as tf
+    tf.disable_v2_behavior()
+except ImportError:
+    import tensorflow as tf
 import numpy as np
 from tvm import relay
 from tvm.relay.frontend.tensorflow import from_tensorflow

tests/python/frontend/tensorflow/test_no_op.py

@@ -15,7 +15,10 @@
 # specific language governing permissions and limitations
 # under the License.
 """Unit tests for converting TensorFlow debugging ops to Relay."""
-import tensorflow as tf
+try:
+    import tensorflow.compat.v1 as tf
+except ImportError:
+    import tensorflow as tf
 import numpy as np
 from tvm import relay
 from tvm.relay.frontend.tensorflow import from_tensorflow

tests/python/frontend/tflite/test_forward.py

@@ -26,7 +26,10 @@ import numpy as np
 import tvm
 from tvm import te
 from tvm import relay
-import tensorflow as tf
+try:
+    import tensorflow.compat.v1 as tf
+except ImportError:
+    import tensorflow as tf
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import ops
 from tensorflow.python.ops import math_ops
@@ -156,7 +159,7 @@ def compare_tflite_with_tvm(in_data, in_name, input_tensors,
         if init_global_variables:
             sess.run(variables.global_variables_initializer())
         # convert to tflite model
-        converter = interpreter_wrapper.TFLiteConverter.from_session(
+        converter = tf.lite.TFLiteConverter.from_session(
             sess, input_tensors, output_tensors)
 
         if quantized:

tutorials/frontend/from_tflite.py

@@ -99,8 +99,12 @@ tflite_model_file = os.path.join(model_dir, "mobilenet_v1_1.0_224.tflite")
 tflite_model_buf = open(tflite_model_file, "rb").read()
 
 # Get TFLite model from buffer
-import tflite.Model
-tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
+try:
+    import tflite
+    tflite_model = tflite.Model.GetRootAsModel(tflite_model_buf, 0)
+except AttributeError:
+    import tflite.Model
+    tflite_model = tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
 
 ######################################################################
 # Load a test image