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Remove unnecessary lambda expression #1428

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Merged
wyli merged 3 commits into from
Jan 11, 2021
Merged

Remove unnecessary lambda expression #1428

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e855348
Remove unnecessary lambda expression
deepsource-autofix[bot] Jan 11, 2021
0b033d7
fixes compatible attributes in config printing
wyli Jan 11, 2021
4ecb432
Merge branch 'master' into deepsource-fix-a5f66533
wyli Jan 11, 2021
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25 changes: 13 additions & 12 deletions monai/config/deviceconfig.py
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Original file line number Diff line number Diff line change
Expand Up @@ -123,31 +123,31 @@ def get_system_info() -> OrderedDict:
"""
output: OrderedDict = OrderedDict()

_dict_append(output, "System", lambda: platform.system())
_dict_append(output, "System", platform.system)
if output["System"] == "Windows":
_dict_append(output, "Win32 version", lambda: platform.win32_ver())
_dict_append(output, "Win32 version", platform.win32_ver)
if hasattr(platform, "win32_edition"):
_dict_append(output, "Win32 edition", lambda: platform.win32_edition()) # type:ignore[attr-defined]
_dict_append(output, "Win32 edition", platform.win32_edition) # type:ignore[attr-defined]
elif output["System"] == "Darwin":
_dict_append(output, "Mac version", lambda: platform.mac_ver()[0])
else:
linux_ver = re.search(r'PRETTY_NAME="(.*)"', open("/etc/os-release", "r").read())
if linux_ver:
_dict_append(output, "Linux version", lambda: linux_ver.group(1))

_dict_append(output, "Platform", lambda: platform.platform())
_dict_append(output, "Processor", lambda: platform.processor())
_dict_append(output, "Machine", lambda: platform.machine())
_dict_append(output, "Python version", lambda: platform.python_version())
_dict_append(output, "Platform", platform.platform)
_dict_append(output, "Processor", platform.processor)
_dict_append(output, "Machine", platform.machine)
_dict_append(output, "Python version", platform.python_version)

if not has_psutil:
_dict_append(output, "`psutil` missing", lambda: "run `pip install monai[psutil]`")
else:
p = psutil.Process()
with p.oneshot():
_dict_append(output, "Process name", lambda: p.name())
_dict_append(output, "Command", lambda: p.cmdline())
_dict_append(output, "Open files", lambda: p.open_files())
_dict_append(output, "Process name", p.name)
_dict_append(output, "Command", p.cmdline)
_dict_append(output, "Open files", p.open_files)
_dict_append(output, "Num physical CPUs", lambda: psutil.cpu_count(logical=False))
_dict_append(output, "Num logical CPUs", lambda: psutil.cpu_count(logical=True))
_dict_append(output, "Num usable CPUs", lambda: len(psutil.Process().cpu_affinity()))
Expand Down Expand Up @@ -204,8 +204,9 @@ def get_gpu_info() -> OrderedDict:
_dict_append(output, "cuDNN version", lambda: cudnn_ver)

if num_gpus > 0:
_dict_append(output, "Current device", lambda: torch.cuda.current_device())
_dict_append(output, "Library compiled for CUDA architectures", lambda: torch.cuda.get_arch_list())
_dict_append(output, "Current device", torch.cuda.current_device)
if hasattr(torch.cuda, "get_arch_list"): # get_arch_list is new in torch 1.7.1
_dict_append(output, "Library compiled for CUDA architectures", torch.cuda.get_arch_list)
for gpu in range(num_gpus):
_dict_append(output, "Info for GPU", gpu)
gpu_info = torch.cuda.get_device_properties(gpu)
Expand Down
2 changes: 1 addition & 1 deletion tests/test_activations.py
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Expand Up @@ -32,7 +32,7 @@
]

TEST_CASE_3 = [
{"sigmoid": False, "softmax": False, "other": lambda x: torch.tanh(x)},
{"sigmoid": False, "softmax": False, "other": torch.tanh},
torch.tensor([[[[0.0, 1.0], [2.0, 3.0]]]]),
torch.tensor([[[[0.0000, 0.7616], [0.9640, 0.9951]]]]),
(1, 1, 2, 2),
Expand Down
4 changes: 2 additions & 2 deletions tests/test_activationsd.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@
]

TEST_CASE_2 = [
{"keys": ["pred", "label"], "sigmoid": False, "softmax": False, "other": [lambda x: torch.tanh(x), None]},
{"keys": ["pred", "label"], "sigmoid": False, "softmax": False, "other": [torch.tanh, None]},
{"pred": torch.tensor([[[[0.0, 1.0], [2.0, 3.0]]]]), "label": torch.tensor([[[[0.0, 1.0], [2.0, 3.0]]]])},
{
"pred": torch.tensor([[[[0.0000, 0.7616], [0.9640, 0.9951]]]]),
Expand All @@ -37,7 +37,7 @@
]

TEST_CASE_3 = [
{"keys": "pred", "sigmoid": False, "softmax": False, "other": lambda x: torch.tanh(x)},
{"keys": "pred", "sigmoid": False, "softmax": False, "other": torch.tanh},
{"pred": torch.tensor([[[[0.0, 1.0], [2.0, 3.0]]]])},
{"pred": torch.tensor([[[[0.0000, 0.7616], [0.9640, 0.9951]]]])},
(1, 1, 2, 2),
Expand Down
4 changes: 2 additions & 2 deletions tests/test_data_stats.py
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Expand Up @@ -78,7 +78,7 @@
"data_shape": True,
"value_range": True,
"data_value": True,
"additional_info": lambda x: np.mean(x),
"additional_info": np.mean,
"logger_handler": None,
},
np.array([[0, 1], [1, 2]]),
Expand Down Expand Up @@ -124,7 +124,7 @@ def test_file(self, input_data, expected_print):
"data_shape": True,
"value_range": True,
"data_value": True,
"additional_info": lambda x: np.mean(x),
"additional_info": np.mean,
"logger_handler": handler,
}
transform = DataStats(**input_param)
Expand Down
6 changes: 3 additions & 3 deletions tests/test_data_statsd.py
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Expand Up @@ -79,7 +79,7 @@
"data_shape": True,
"value_range": True,
"data_value": True,
"additional_info": lambda x: np.mean(x),
"additional_info": np.mean,
},
{"img": np.array([[0, 1], [1, 2]])},
"test data statistics:\nShape: (2, 2)\nValue range: (0, 2)\nValue: [[0 1]\n [1 2]]\nAdditional info: 1.0",
Expand Down Expand Up @@ -108,7 +108,7 @@
"data_shape": True,
"value_range": (True, False),
"data_value": (False, True),
"additional_info": (lambda x: np.mean(x), None),
"additional_info": (np.mean, None),
},
{"img": np.array([[0, 1], [1, 2]]), "affine": np.eye(2, 2)},
"affine statistics:\nShape: (2, 2)\nValue: [[1. 0.]\n [0. 1.]]",
Expand Down Expand Up @@ -138,7 +138,7 @@ def test_file(self, input_data, expected_print):
"data_shape": True,
"value_range": True,
"data_value": True,
"additional_info": lambda x: np.mean(x),
"additional_info": np.mean,
"logger_handler": handler,
}
transform = DataStatsd(**input_param)
Expand Down