from keras.backend import tensorflow_backend as tf
from keras.backend import floatx
sys.path = [sys.path[-1]] + sys.path[:-1]
import plaidml
from plaidml.keras import backend as pkb
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--fp16', action='store_true')
parser.add_argument('-v', '--verbose', action='count', default=0)
args, remainder = parser.parse_known_args()
plaidml._internal_set_vlog(args.verbose)
if args.fp16:
pkb.set_floatx('float16')
DEFAULT_TOL = 1e-2
DEFAULT_ATOL = 1e-5
else:
pkb.set_floatx('float32')
DEFAULT_TOL = 1e-3
DEFAULT_ATOL = 1e-8
def opTest(in_data,
tol=DEFAULT_TOL,
atol=DEFAULT_ATOL,
skip_tensorflow=False,
verbose=False,
input_shapes=None):
# If using with non-tensor parameters, all tensor params must appear before
theano.config.optimizer = "None"
# We have to set_floatx before the interpreter encounters any of the test
# functions, because it will execute the 'opTest' decorator as it processes
# each test function, which will execute the value-generation functions, which
# will use the value of floatx() to create test data. Changing floatx later
# will have inconsistent effects.
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--fp16', action='store_true')
parser.add_argument('-v', '--verbose', action='count', default=0)
args, remainder = parser.parse_known_args()
plaidml._internal_set_vlog(args.verbose)
if args.fp16:
set_floatx('float16')
DEFAULT_TOL = 1e-2
DEFAULT_ATOL = 1e-5
else:
set_floatx('float32')
DEFAULT_TOL = 1e-3
DEFAULT_ATOL = 1e-8
def m(*args, **kwargs):
dtype = kwargs.get('dtype', floatx())
"""Makes a test matrix whose dimensions are the supplied arguments."""
total = functools.reduce(operator.mul, args, 1)
arr = np.array(range(-2, total-2), dtype=dtype)
arr = np.reshape(arr, args)
return arr