def string_to_number_v1(string_tensor=None,
out_type=dtypes.float32,
name=None,
input=None):
string_tensor = deprecation.deprecated_argument_lookup(
"input", input, "string_tensor", string_tensor)
return gen_parsing_ops.string_to_number(string_tensor, out_type, name)
def _tf_int(x, base):
if base not in (10, UNSPECIFIED):
raise NotImplementedError('base {} not supported for int'.format(base))
# TODO(mdan): We shouldn't assume int32.
if x.dtype == dtypes.string:
return gen_parsing_ops.string_to_number(x, out_type=dtypes.int32)
return math_ops.cast(x, dtype=dtypes.int32)
def _tf_int(x, base):
if base not in (10, UNSPECIFIED):
raise NotImplementedError('base {} not supported for int'.format(base))
# TODO(mdan): We shouldn't assume int32.
if x.dtype == dtypes.string:
return gen_parsing_ops.string_to_number(x, out_type=dtypes.int32)
return math_ops.cast(x, dtype=dtypes.int32)
def string_to_number_v1(
string_tensor=None,
out_type=dtypes.float32,
name=None,
input=None):
string_tensor = deprecation.deprecated_argument_lookup(
"input", input, "string_tensor", string_tensor)
return gen_parsing_ops.string_to_number(string_tensor, out_type, name)
def string_to_number(input, out_type=dtypes.float32, name=None):
r"""Converts each string in the input Tensor to the specified numeric type.
(Note that int32 overflow results in an error while float overflow
results in a rounded value.)
Args:
input: A `Tensor` of type `string`.
out_type: An optional `tf.DType` from: `tf.float32, tf.float64, tf.int32,
tf.int64`. Defaults to `tf.float32`.
The numeric type to interpret each string in `string_tensor` as.
name: A name for the operation (optional).
Returns:
A `Tensor` of type `out_type`.
"""
return gen_parsing_ops.string_to_number(input, out_type, name)
def string_to_number(input, out_type=dtypes.float32, name=None):
r"""Converts each string in the input Tensor to the specified numeric type.
(Note that int32 overflow results in an error while float overflow
results in a rounded value.)
Args:
input: A `Tensor` of type `string`.
out_type: An optional `tf.DType` from: `tf.float32, tf.float64, tf.int32,
tf.int64`. Defaults to `tf.float32`.
The numeric type to interpret each string in `string_tensor` as.
name: A name for the operation (optional).
Returns:
A `Tensor` of type `out_type`.
"""
return gen_parsing_ops.string_to_number(input, out_type, name)
def _tf_float(x):
# TODO(mdan): We shouldn't assume float32.
if x.dtype == dtypes.string:
return gen_parsing_ops.string_to_number(x, out_type=dtypes.float32)
return math_ops.cast(x, dtype=dtypes.float32)
def _tf_float(x):
# TODO(mdan): We shouldn't assume float32.
if x.dtype == dtypes.string:
return gen_parsing_ops.string_to_number(x, out_type=dtypes.float32)
return math_ops.cast(x, dtype=dtypes.float32)
