def testTensorArrayReadWrongIndexOrDataTypeFails(self):
with self.test_session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
dtype=dtypes.float32, 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=dtypes.float64, flow_in=w0.flow)
with self.assertRaisesOpError(
"TensorArray dtype is float but Op requested dtype double."):
r0_bad.eval()
# Test reading from a different index than the one we wrote to
r1 = w0.read(1)
with self.assertRaisesOpError(
"Could not read from TensorArray index 1 because "
"it has not yet been written to."):
r1.eval()
# Test reading from a negative index
with self.assertRaisesOpError(
r"Tried to read from index -1 but array size is: 3"):
ta.read(-1).eval()
# Test reading from too large an index
with self.assertRaisesOpError(
"Tried to read from index 3 but array size is: 3"):
ta.read(3).eval()
def testTensorArrayReadWrongIndexOrDataTypeFails(self):
with self.test_session(use_gpu=True):
ta = tensor_array_ops.TensorArray(
dtype=dtypes.float32, 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=dtypes.float64, flow_in=w0.flow)
with self.assertRaisesOpError(
"TensorArray dtype is float but Op requested dtype double."):
r0_bad.eval()
# Test reading from a different index than the one we wrote to
r1 = w0.read(1)
with self.assertRaisesOpError(
"Could not read from TensorArray index 1 because "
"it has not yet been written to."):
r1.eval()
# Test reading from a negative index
with self.assertRaisesOpError(
r"Tried to read from index -1 but array size is: 3"):
ta.read(-1).eval()
# Test reading from too large an index
with self.assertRaisesOpError(
"Tried to read from index 3 but array size is: 3"):
ta.read(3).eval()
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 testTensorArrayReadWrongIndexOrDataTypeFails(self):
with self.test_session(), self.test_scope():
ta = tensor_array_ops.TensorArray(
dtype=dtypes.float32, 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=dtypes.float64, flow_in=w0.flow)
with self.assertRaisesOpError(
"TensorArray dtype is float but op has dtype double."):
r0_bad.eval()
# Test reading from a different index than the one we wrote to
w0.read(1)
def read(self, index, name=None):
"""Read the value at location `index` in the TensorArray.
Args:
index: 0-D. int32 tensor with the index to read from.
name: A name for the operation (optional).
Returns:
The tensor at index `index`.
"""
with ops.colocate_with(self._handle):
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):
"""Read the value at location `index` in the TensorArray.
Args:
index: 0-D. int32 tensor with the index to read from.
name: A name for the operation (optional).
Returns:
The tensor at index `index`.
"""
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 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)
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 = self.float_types[0]
dtype2 = self.float_types[1]
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)