121 lines
5.0 KiB
Python
121 lines
5.0 KiB
Python
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## @package device_checker
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# Module caffe2.python.device_checker
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import numpy as np
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import copy
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from caffe2.python import workspace
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from caffe2.python.core import InferOpBlobDevicesAsDict
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from future.utils import viewitems
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class DeviceChecker(object):
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"""A device checker in Python to check consistency across multiple devices.
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This is not the most efficient way to check devices, as the Python interface
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will involve a lot of copies back and forth operations. Use at your own risk.
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"""
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def __init__(self, threshold, device_options):
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self._threshold = threshold
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self._device_options = device_options
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def CheckSimple(self, op, inputs, outputs_to_check,
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input_device_options=None):
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"""Checks the operator with different device implementations.
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Inputs:
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op: the operator to be checked.
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inputs: the input data in numpy arrays.
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outputs_to_check: the outputs to check between devices.
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input_device_options: a mapping from input name to a device to use
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(instead of self._device_options)
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Outputs:
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boolean: True if it passes, False if it does not pass.
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"""
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op = copy.deepcopy(op)
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# Entering the checker workspace
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old_ws_name = workspace.CurrentWorkspace()
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results = []
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workspace.SwitchWorkspace("_device_check_", True)
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for i, device_option in enumerate(self._device_options):
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op.device_option.CopyFrom(device_option)
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_input_device_options = input_device_options or \
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InferOpBlobDevicesAsDict(op)[0]
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print(_input_device_options)
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for i, arr in enumerate(inputs):
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workspace.FeedBlob(
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op.input[i], np.array(arr),
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_input_device_options.get(op.input[i], device_option)
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)
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workspace.RunOperatorOnce(op)
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results.append(
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[workspace.FetchBlob(op.output[idx])
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for idx in outputs_to_check])
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# Everything is done, reset the workspace.
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workspace.ResetWorkspace()
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# After running on all devices, check correctness
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success = True
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for i in range(1, len(self._device_options)):
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for j in range(len(outputs_to_check)):
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x = results[i][j]
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y = results[0][j]
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if not np.allclose(x, y,
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atol=self._threshold, rtol=self._threshold):
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print('Failure in checking device option {}'
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' and output {}. The outputs are:'
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.format(i, op.output[outputs_to_check[j]]))
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print(x.flatten())
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print(y.flatten())
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print(np.max(np.abs(x - y)))
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success = False
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# else:
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# print ('Passed device pair (0, %d), %s %s' %
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# (i, outputs_to_check[j], y.shape))
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workspace.SwitchWorkspace(old_ws_name)
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return success
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def CheckNet(self, net, inputs=None, blobs_to_check=None, ignore=None):
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"""Checks a network by inspecting all of its intermediate results, and
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see if things match.
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"""
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if inputs is None:
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inputs = {}
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if ignore is None:
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ignore = set()
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old_ws_name = workspace.CurrentWorkspace()
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results = []
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if blobs_to_check is None:
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blobs_to_check = sum([list(op.output) for op in net.op], [])
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blobs_to_check = [b for b in blobs_to_check if b not in ignore]
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workspace.SwitchWorkspace("_device_check_", True)
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for device_option in self._device_options:
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for name, arr in viewitems(inputs):
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# print 'feeding', name
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workspace.FeedBlob(name, arr, device_option)
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for op in net.op:
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op.device_option.CopyFrom(device_option)
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workspace.RunNetOnce(net)
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results.append(
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[workspace.FetchBlob(name) for name in blobs_to_check]
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)
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# After running on all devices, check correctness
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success = True
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for i in range(1, len(results)):
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for j in range(len(blobs_to_check)):
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x = results[i][j]
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y = results[0][j]
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if not np.allclose(x, y,
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atol=self._threshold, rtol=self._threshold):
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print('Failure in checking device option {}'
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' and output {}. The outputs are:'
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.format(i, blobs_to_check[j]))
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print(x.flatten())
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print(y.flatten())
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print(np.max(np.abs(x - y)))
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success = False
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# else:
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# print ('Passed device pair (%d, %d), %s %s: %s' %
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# (i, j, blobs_to_check[j], y.shape,
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# str(y.flatten())))
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workspace.SwitchWorkspace(old_ws_name)
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return success
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