onnxruntime-tvm/topi/tests/python/test_topi_math.py

131 строка
4.6 KiB
Python

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import numpy as np
import tvm
import topi
import topi.testing
from topi import util
from common import get_all_backend
def test_util():
x = tvm.const(100, "int32")
assert util.get_const_int(x) == 100
assert util.get_const_tuple((x, x)) == (100, 100)
def test_ewise():
def test_apply(
func,
name,
f_numpy,
low,
high,
shape=(20, 3),
dtype=tvm.float32,
check_round=False,
skip_name_check=False,
):
m = tvm.var("m")
l = tvm.var("l")
A = tvm.placeholder((m, l), dtype=dtype, name="A")
B = func(A)
assert tuple(B.shape) == tuple(A.shape)
if not skip_name_check:
assert B.op.body[0].name == name
a_np = np.random.uniform(low=low, high=high, size=shape).astype(A.dtype) * 10
# avoid round check too close to boundary
if check_round:
a_np += ((np.fmod(a_np, 1) - 0.5) < 1e-6) * 1e-5
b_np = f_numpy(a_np)
def check_device(device):
ctx = tvm.context(device, 0)
if not ctx.exist:
print("Skip because %s is not enabled" % device)
return
print("Running on target: %s" % device)
with tvm.target.create(device):
s = topi.generic.schedule_injective(B)
foo = tvm.build(s, [A, B], device, name=name)
a = tvm.nd.array(a_np, ctx)
b = tvm.nd.array(np.zeros_like(b_np), ctx)
foo(a, b)
tvm.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5, atol=1e-5)
for device in get_all_backend():
check_device(device)
test_apply(topi.floor, "floor", np.floor, -100, 100)
test_apply(topi.ceil, "ceil", np.ceil, -100, 100)
test_apply(topi.sign, "sign", np.sign, -100, 100, skip_name_check=True)
test_apply(topi.trunc, "trunc", np.trunc, -100, 100)
test_apply(topi.abs, "fabs", np.abs, -100, 100)
test_apply(topi.round, "round", np.round, -100, 100, check_round=True)
test_apply(topi.exp, "exp", np.exp, -1, 1)
test_apply(topi.tanh, "tanh", np.tanh, -10, 10, shape=(128, 128))
test_apply(topi.tanh, "tanh", np.tanh, -10, 10, shape=(128, 128), dtype="float64")
test_apply(topi.sigmoid, "sigmoid", lambda x: 1 / (1 + np.exp(-x)), -1, 1)
test_apply(topi.log, "log", np.log, 0, 100)
test_apply(topi.sqrt, "sqrt", np.sqrt, 0, 100)
test_apply(topi.rsqrt, "rsqrt", lambda x: np.ones_like(x) / np.sqrt(x), 0, 100, skip_name_check=True)
def test_cast():
def verify(from_dtype, to_dtype, low=-100, high=100):
shape = (5, 4)
A = tvm.placeholder(shape, dtype=from_dtype, name="A")
B = topi.cast(A, to_dtype)
if from_dtype == "bool":
a_np = np.random.choice([True, False], size=shape)
else:
a_np = np.random.uniform(low, high, size=shape).astype(from_dtype)
if to_dtype == "bool":
a_np = a_np - a_np[2, 3]
b_np = a_np.astype(to_dtype)
for device in get_all_backend():
ctx = tvm.context(device, 0)
if not ctx.exist:
print("Skip because %s is not enabled" % device)
continue
print("Running on target: %s" % device)
with tvm.target.create(device):
s = topi.generic.schedule_injective(B)
foo = tvm.build(s, [A, B], device)
a = tvm.nd.array(a_np, ctx)
b = tvm.nd.empty(shape=shape, dtype=to_dtype, ctx=ctx)
foo(a, b)
tvm.testing.assert_allclose(b.asnumpy(), b_np)
verify("int32", "float32")
verify("int32", "float64")
verify("int32", "bool")
verify("float32", "int32")
verify("float32", "float64")
verify("float32", "bool")
verify("bool", "float32")
verify("bool", "int32")
if __name__ == "__main__":
test_util()
test_ewise()
test_cast()