def fn(): ta = tensor_array_ops.TensorArray( dtype=dtype1, tensor_array_name="foo", size=3) w0 = ta.write(0, math_ops.cast([[4.0, 5.0]], dtype1)) # Test reading wrong datatype. return gen_data_flow_ops.tensor_array_read_v3( handle=w0.handle, index=0, dtype=dtype2, flow_in=w0.flow)
def read(self, index, name=None): """See TensorArray.""" value = gen_data_flow_ops.tensor_array_read_v3(handle=self._handle, index=index, flow_in=self._flow, dtype=self._dtype, name=name) if self._element_shape: value.set_shape(self._element_shape[0].dims) return value
def read(self, index, name=None): """See TensorArray.""" value = gen_data_flow_ops.tensor_array_read_v3( handle=self._handle, index=index, flow_in=self._flow, dtype=self._dtype, name=name) if self._element_shape: value.set_shape(self._element_shape[0].dims) return value
def fn(): ta = tensor_array_ops.TensorArray(dtype=dtype1, tensor_array_name="foo", size=3) w0 = ta.write(0, math_ops.cast([[4.0, 5.0]], dtype1)) # Test reading wrong datatype. return gen_data_flow_ops.tensor_array_read_v3( handle=w0.handle, index=0, dtype=dtype2, flow_in=w0.flow)
def testTensorArrayReadWrongIndexOrDataTypeFails(self): # Find two different floating point types, create an array of # the first type, but try to read the other type. if len(self.float_types) > 1: dtype1, dtype2 = list(self.float_types)[:2] with self.test_session(), self.test_scope(): ta = tensor_array_ops.TensorArray( dtype=dtype1, tensor_array_name="foo", size=3) w0 = ta.write(0, [[4.0, 5.0]]) # Test reading wrong datatype. r0_bad = gen_data_flow_ops.tensor_array_read_v3( handle=w0.handle, index=0, dtype=dtype2, flow_in=w0.flow) with self.assertRaisesOpError("TensorArray dtype is "): r0_bad.eval() # Test reading from a different index than the one we wrote to w0.read(1)