fix np.cast

Signed-off-by: xadupre <[email protected]>

Author: xadupre

.github/actions/keras_application_test/action.yml

@@ -46,6 +46,7 @@ runs:
           pip install git+https://github.com/qubvel/efficientnet
           pip install keras-self-attention
           pip install pytest pytest-cov pytest-runner
+          pip uninstall -y protobuf
 
           if [[ ${{ inputs.tf_version }} == 1.* ]]; then 
               pip install keras==2.3.1
@@ -60,7 +61,7 @@ runs:
                 pip install tf_keras==${{ inputs.tf_version }} tensorflow==${{ inputs.tf_version }}
               else
                 echo "-- install-1 TF ${{ inputs.tf_version }}"
-                pip install "protobuf<3.20" tensorflow==${{ inputs.tf_version }}
+                pip install protobuf tensorflow==${{ inputs.tf_version }}
               fi
           fi
 

.github/actions/keras_unit_test/action.yml

@@ -39,7 +39,7 @@ runs:
                 pip install tf_keras==${{ inputs.tf_version }} tensorflow==${{ inputs.tf_version }}
               else
                 echo "-- install-2 TF ${{ inputs.tf_version }}"
-                pip install "protobuf<3.20" tensorflow==${{ inputs.tf_version }}
+                pip install protobuf tensorflow==${{ inputs.tf_version }}
               fi
           fi
 

tests/test_custom_rnncell.py

@@ -16,6 +16,7 @@
 # pylint: disable=abstract-method,arguments-differ
 
 if is_tf2():
+    # no test for tf2 in this file
     pass
 else:
     LSTMBlockCell = tf.contrib.rnn.LSTMBlockCell
@@ -26,6 +27,45 @@
     dynamic_rnn = tf.nn.dynamic_rnn
     bidirectional_dynamic_rnn = tf.nn.bidirectional_dynamic_rnn
 
+    class GatedGRUCell(RNNCell):
+        def __init__(self, hidden_dim, reuse=None):
+            super().__init__(self, _reuse=reuse)
+            self._num_units = hidden_dim
+            self._activation = tf.tanh
+
+        @property
+        def state_size(self):
+            return self._num_units
+
+        @property
+        def output_size(self):
+            return self._num_units
+
+        def call(self, inputs, state):
+            # inputs shape: [batch size, time step, input size] = [1, 3, 2]
+            # num_units: 5
+            # W shape: [2, 3 * 5] = [2, 15]
+            # U shape: [5, 3 * 5] = [5, 15]
+            # b shape: [1, 3 * 5] = [1, 15]
+            # state shape: [batch size, state size] = [1, 5]
+
+            input_dim = inputs.get_shape()[-1]
+            assert input_dim is not None, "input dimension must be defined"
+            # W = tf.get_variable(name="W", shape=[input_dim, 3 * self._num_units], dtype=tf.float32)
+            W = np.arange(30.0, dtype=np.float32).reshape((2, 15))
+            # U = tf.get_variable(name='U', shape=[self._num_units, 3 * self._num_units], dtype=tf.float32)
+            U = np.arange(75.0, dtype=np.float32).reshape((5, 15))
+            # b = tf.get_variable(name='b', shape=[1, 3 * self._num_units], dtype=tf.float32)
+            b = np.arange(15.0, dtype=np.float32).reshape((1, 15))
+
+            xw = tf.split(tf.matmul(inputs, W) + b, 3, 1)
+            hu = tf.split(tf.matmul(state, U), 3, 1)
+            r = tf.sigmoid(xw[0] + hu[0])
+            z = tf.sigmoid(xw[1] + hu[1])
+            h1 = self._activation(xw[2] + r * hu[2])
+            next_h = h1 * (1 - z) + state * z
+            return next_h, next_h
+
 
 class CustomRnnCellTests(Tf2OnnxBackendTestBase):
     @check_opset_min_version(8, "Scan")
@@ -370,45 +410,5 @@ def func(encoder_x, decoder_x, seq_length):
         self.run_test_case(func, feed_dict, input_names_with_port, output_names_with_port, 0.1)
 
 
-class GatedGRUCell(RNNCell):
-    def __init__(self, hidden_dim, reuse=None):
-        super().__init__(self, _reuse=reuse)
-        self._num_units = hidden_dim
-        self._activation = tf.tanh
-
-    @property
-    def state_size(self):
-        return self._num_units
-
-    @property
-    def output_size(self):
-        return self._num_units
-
-    def call(self, inputs, state):
-        # inputs shape: [batch size, time step, input size] = [1, 3, 2]
-        # num_units: 5
-        # W shape: [2, 3 * 5] = [2, 15]
-        # U shape: [5, 3 * 5] = [5, 15]
-        # b shape: [1, 3 * 5] = [1, 15]
-        # state shape: [batch size, state size] = [1, 5]
-
-        input_dim = inputs.get_shape()[-1]
-        assert input_dim is not None, "input dimension must be defined"
-        # W = tf.get_variable(name="W", shape=[input_dim, 3 * self._num_units], dtype=tf.float32)
-        W = np.arange(30.0, dtype=np.float32).reshape((2, 15))
-        # U = tf.get_variable(name='U', shape=[self._num_units, 3 * self._num_units], dtype=tf.float32)
-        U = np.arange(75.0, dtype=np.float32).reshape((5, 15))
-        # b = tf.get_variable(name='b', shape=[1, 3 * self._num_units], dtype=tf.float32)
-        b = np.arange(15.0, dtype=np.float32).reshape((1, 15))
-
-        xw = tf.split(tf.matmul(inputs, W) + b, 3, 1)
-        hu = tf.split(tf.matmul(state, U), 3, 1)
-        r = tf.sigmoid(xw[0] + hu[0])
-        z = tf.sigmoid(xw[1] + hu[1])
-        h1 = self._activation(xw[2] + r * hu[2])
-        next_h = h1 * (1 - z) + state * z
-        return next_h, next_h
-
-
 if __name__ == '__main__':
     unittest_main()

tests/utils/setup_test_env.sh

@@ -17,16 +17,18 @@ echo "==== ONNX version: $ONNX_VERSION"
 
 pip install pytest pytest-cov pytest-runner coverage graphviz requests pyyaml pillow pandas parameterized sympy coloredlogs flatbuffers timeout-decorator
 pip uninstall -y tensorflow
-pip install onnx==$ONNX_VERSION onnxruntime==$ORT_VERSION onnxruntime-extensions "tensorflow-text<=$TF_VERSION" tensorflow==$TF_VERSION
+pip install onnx==$ONNX_VERSION onnxruntime==$ORT_VERSION onnxruntime-extensions
 
 if [[ $TF_VERSION == 1.* ]]; then 
     pip install numpy==1.19.0
 else 
+    pip uninstall -y protobuf
     if [[ "$TF_VERSION" != "2.13.0" && "$TF_VERSION" != "2.9.0" ]]; then 
         echo "-- install-3 TF-KERAS $TF_VERSION"
-        pip install tf_keras==$TF_VERSION
+        pip install tf_keras==$TF_VERSION "tensorflow-text<=$TF_VERSION"
     else
         echo "-- install-3 TF $TF_VERSION"
+        pip install "tensorflow-text<=$TF_VERSION" tensorflow==$TF_VERSION protobuf
     fi
 fi
 

tf2onnx/tfonnx.py

@@ -74,7 +74,7 @@ def rewrite_constant_fold(g, ops):
     func_map = {
         "Add": np.add,
         "GreaterEqual": np.greater_equal,
-        "Cast": np.cast,
+        "Cast": lambda x, dtype: x.astype(dtype),
         "ConcatV2": np.concatenate,
         "Less": np.less,
         "ListDiff": np.setdiff1d,