def pipeline_arithm_ops_cpu(source):
data = fn.external_source(source=source, layout="HWC")
processed = (data * 2,
data + 2,
data - 2,
data / 2,
data // 2,
data ** 2,
data == 2,
data != 2,
data < 2,
data <= 2,
data > 2,
data >= 2,
data & 2,
data | 2,
data ^ 2,
dmath.abs(data),
dmath.fabs(data),
dmath.floor(data),
dmath.ceil(data),
dmath.pow(data, 2),
dmath.fpow(data, 1.5),
dmath.min(data, 2),
dmath.max(data, 50),
dmath.clamp(data, 10, 50),
dmath.sqrt(data),
dmath.rsqrt(data),
dmath.cbrt(data),
dmath.exp(data),
dmath.exp(data),
dmath.log(data),
dmath.log2(data),
dmath.log10(data),
dmath.sin(data),
dmath.cos(data),
dmath.tan(data),
dmath.asin(data),
dmath.acos(data),
dmath.atan(data),
dmath.atan2(data, 3),
dmath.sinh(data),
dmath.cosh(data),
dmath.tanh(data),
dmath.asinh(data),
dmath.acosh(data),
dmath.atanh(data))
return processed
def test_arithm_ops_cpu():
pipe = Pipeline(batch_size=batch_size, num_threads=4, device_id=None)
data = fn.external_source(source=get_data, layout="HWC")
processed = [
data * 2, data + 2, data - 2, data / 2, data // 2, data**2, data == 2,
data != 2, data < 2, data <= 2, data > 2, data >= 2, data & 2,
data | 2, data ^ 2,
dmath.abs(data),
dmath.fabs(data),
dmath.floor(data),
dmath.ceil(data),
dmath.pow(data, 2),
dmath.fpow(data, 1.5),
dmath.min(data, 2),
dmath.max(data, 50),
dmath.clamp(data, 10, 50),
dmath.sqrt(data),
dmath.rsqrt(data),
dmath.cbrt(data),
dmath.exp(data),
dmath.exp(data),
dmath.log(data),
dmath.log2(data),
dmath.log10(data),
dmath.sin(data),
dmath.cos(data),
dmath.tan(data),
dmath.asin(data),
dmath.acos(data),
dmath.atan(data),
dmath.atan2(data, 3),
dmath.sinh(data),
dmath.cosh(data),
dmath.tanh(data),
dmath.asinh(data),
dmath.acosh(data),
dmath.atanh(data)
]
pipe.set_outputs(*processed)
pipe.build()
for _ in range(3):
pipe.run()
((lambda x: math.tanh(x)), (lambda x: np.tanh(x)), "tanh", default_range, 1e-6),
((lambda x: math.asinh(x)), (lambda x: np.arcsinh(x)), "asinh", limited_range, 1e-6),
((lambda x: math.acosh(x)), (lambda x: np.arccosh(x)), "acosh", pos_range, 1e-6),
((lambda x: math.atanh(x)), (lambda x: np.arctanh(x)), "atanh", one_range, 1e-6)]
sane_operations = [((lambda x, y: x + y), "+", default_range),
((lambda x, y: x - y), "-", default_range),
((lambda x, y: x * y), "*", default_range),
(((lambda x, y: x ** y), sane_pow), "**", pow_range),
(((lambda x, y: math.pow(x, y)), sane_pow), "pow", pow_range),
(((lambda x, y: math.min(x, y)), (lambda x, y: np.minimum(x, y))), "min", default_range),
(((lambda x, y: math.max(x, y)), (lambda x, y: np.maximum(x, y))), "max", default_range)]
floaty_operations = [(((lambda x, y: x / y), (lambda x, y: x / y)), "/", default_range),
(((lambda x, y: math.fpow(x, y)), sane_pow), "fpow", pow_range),
(((lambda x, y: math.atan2(x, y)), (lambda x, y: np.arctan2(x, y))), "atan2", default_range)]
bitwise_operations = [((lambda x, y: x & y), "&"), ((lambda x, y: x | y), "|"),
((lambda x, y: x ^ y), "^")]
comparisons_operations = [((lambda x, y: x == y), "=="), ((lambda x, y: x != y), "!="),
((lambda x, y: x < y), "<"), ((lambda x, y: x <= y), "<="),
((lambda x, y: x > y), ">"), ((lambda x, y: x >= y), ">="),]
# The observable behaviour for hi < lo is the same as numpy
ternary_operations = [(((lambda v, lo, hi: math.clamp(v, lo, hi)), (lambda v, lo, hi: np.clip(v, lo, hi))), "clamp")]
def as_cpu(tl):
if isinstance(tl, TensorListGPU):
return tl.as_cpu()