def check_np_equivalence(fun_name, args, kwargs, array_argnums):
ans_truth = getfun(onp, fun_name)(*args,
**kwargs) # Original numpy, regular args
gnp_fun = getfun(gnp, fun_name)
for dtypes in it.product(*[[gnp.float64, gnp.gpu_float32]] *
len(array_argnums)):
new_args = list(args)
for dtype, argnum in zip(dtypes, array_argnums):
if isinstance(args[argnum], onp.ndarray):
new_args[argnum] = gnp.array(args[argnum], dtype=dtype)
try:
ans_test = gnp_fun(*new_args, **kwargs)
if isinstance(ans_test, gnp.garray):
ans_test = gnp.array(ans_test, dtype=gnp.float64)
assert equivalent_types(ans_truth, ans_test), \
"Type mismatch! \nTruth: {0}, \nResult: {1}\nTypes: {2}, {3}".format(
ans_truth, ans_test, type(ans_truth), type(ans_test))
assert onp.allclose(ans_truth, ans_test, atol=1e-5), \
"Value mismatch.\nTruth: {0}, \nResult: {1}".format(ans_truth, ans_test)
except:
print "Test failed, dtypes were {0} args were {1}, kwargs were {2}".format(
dtypes, args, kwargs)
raise
def check_np_equivalence(fun_name, args, kwargs, array_argnums):
ans_truth = getfun(onp, fun_name)(*args, **kwargs) # Original numpy, regular args
gnp_fun = getfun(gnp, fun_name)
for dtypes in it.product(*[[gnp.float64, gnp.gpu_float32]]*len(array_argnums)):
new_args = list(args)
for dtype, argnum in zip(dtypes, array_argnums):
if isinstance(args[argnum], onp.ndarray):
new_args[argnum] = gnp.array(args[argnum], dtype=dtype)
try:
ans_test = gnp_fun(*new_args, **kwargs)
if isinstance(ans_test, gnp.garray):
ans_test = gnp.array(ans_test, dtype=gnp.float64)
assert equivalent_types(ans_truth, ans_test), \
"Type mismatch! \nTruth: {0}, \nResult: {1}\nTypes: {2}, {3}".format(
ans_truth, ans_test, type(ans_truth), type(ans_test))
assert onp.allclose(ans_truth, ans_test, atol=1e-5), \
"Value mismatch.\nTruth: {0}, \nResult: {1}".format(ans_truth, ans_test)
except:
print "Test failed, dtypes were {0} args were {1}, kwargs were {2}".format(
dtypes, args, kwargs)
raise
def array_from_args(*args):
return np.array(args)
def array(A, *args, **kwargs):
if isinstance(A, np.ndarray):
return np.array(A, *args, **kwargs)
else:
raw_array = np.array(A, *args, **kwargs)
return wrap_if_nodes_inside(raw_array)
def array_from_args(*args):
return np.array(args)
def array(A, *args, **kwargs):
if isinstance(A, np.ndarray):
return np.array(A, *args, **kwargs)
else:
raw_array = np.array(A, *args, **kwargs)
return wrap_if_nodes_inside(raw_array)
def array_from_args(front_shape, *args):
new_array = np.array(args)
return new_array.reshape(front_shape + new_array.shape[1:])
