def real_dtype(dtype):
"""Returns the dtype of the real part."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'real_dtype'):
return dtype.real_dtype
# TODO(jvdillon): Find a better way.
return np.array(0, as_numpy_dtype(dtype)).real.dtype
def min(dtype): # pylint: disable=redefined-builtin
"""Returns the minimum representable value in this data type."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'min'):
return dtype.min
use_finfo = is_floating(dtype) or is_complex(dtype)
return np.finfo(dtype).min if use_finfo else np.iinfo(dtype).min
def is_bool(dtype):
"""Returns whether this is a boolean data type."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'is_bool'):
return dtype.is_bool
# We use `kind` because:
# np.issubdtype(np.uint8, np.bool) == True.
return np.dtype(dtype).kind == 'b'
def name(dtype):
"""Returns the string name for this `dtype`."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'name'):
return dtype.name
if hasattr(dtype, '__name__'):
return dtype.__name__
return str(dtype)
def common_dtype(args_list, dtype_hint=None):
"""Returns explict dtype from `args_list` if there is one."""
dtype = None
for a in tf.nest.flatten(args_list):
if hasattr(a, 'dtype') and a.dtype:
dt = as_numpy_dtype(a.dtype)
else:
continue
if dtype is None:
dtype = dt
elif dtype != dt:
if SKIP_DTYPE_CHECKS:
dtype = (np.ones([2], dtype) + np.ones([2], dt)).dtype
else:
raise TypeError(
'Found incompatible dtypes, {} and {}.'.format(dtype, dt))
return dtype_hint if dtype is None else tf.as_dtype(dtype)
def is_complex(dtype):
"""Returns whether this is a complex floating point type."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'is_complex'):
return dtype.is_complex
return np.issubdtype(np.dtype(dtype), np.complex)
def base_dtype(dtype):
"""Returns a non-reference `dtype` based on this `dtype`."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'base_dtype'):
return dtype.base_dtype
return dtype
def as_numpy_dtype(dtype):
"""Returns a `np.dtype` based on this `dtype`."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'as_numpy_dtype'):
return dtype.as_numpy_dtype
return dtype
def size(dtype):
"""Returns the number of bytes to represent this `dtype`."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'size'):
return dtype.size
return np.dtype(dtype).itemsize
def is_integer(dtype):
"""Returns whether this is a (non-quantized) integer type."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'is_integer') and not callable(dtype.is_integer):
return dtype.is_integer
return np.issubdtype(np.dtype(dtype), np.integer)
def is_floating(dtype):
"""Returns whether this is a (non-quantized, real) floating point type."""
dtype = tf.as_dtype(dtype)
if hasattr(dtype, 'is_floating'):
return dtype.is_floating
return np.issubdtype(np.dtype(dtype), np.float)