Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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import os
# Opt-in checking mode to ensure that we always create numpy arrays using float32
if os.getenv("TEST_ENFORCE_NUMPY_FLOAT32"):
# This file is importer by pytest multiple times, but this breaks the patching
# Removing the env variable seems the easiest way to prevent this.
del os.environ["TEST_ENFORCE_NUMPY_FLOAT32"]
import numpy as np
import traceback
__old_np_array = np.array
__old_np_zeros = np.zeros
__old_np_ones = np.ones
def _check_no_float64(arr, kwargs_dtype):
if arr.dtype == np.float64:
tb = traceback.extract_stack()
# tb[-1] in the stack is this function.
# tb[-2] is the wrapper function, e.g. np_array_no_float64
# we want the calling function, so use tb[-3]
filename = tb[-3].filename
# Only raise if this came from mlagents code
if (
"ml-agents/mlagents" in filename
or "ml-agents-envs/mlagents" in filename
):
raise ValueError(
f"float64 array created. Set dtype=np.float32 instead of current dtype={kwargs_dtype}. "
f"Run pytest with TEST_ENFORCE_NUMPY_FLOAT32=1 to confirm fix."
)
def np_array_no_float64(*args, **kwargs):
res = __old_np_array(*args, **kwargs)
_check_no_float64(res, kwargs.get("dtype"))
return res
def np_zeros_no_float64(*args, **kwargs):
res = __old_np_zeros(*args, **kwargs)
_check_no_float64(res, kwargs.get("dtype"))
return res
def np_ones_no_float64(*args, **kwargs):
res = __old_np_ones(*args, **kwargs)
_check_no_float64(res, kwargs.get("dtype"))
return res
np.array = np_array_no_float64
np.zeros = np_zeros_no_float64
np.ones = np_ones_no_float64