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| from caffe2.python import core, scope |
| from caffe2.proto import caffe2_pb2 |
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| def _get_weights(model, namescope=None): |
| if namescope is None: |
| namescope = scope.CurrentNameScope() |
|
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| if namescope == '': |
| return model.weights[:] |
| else: |
| return [w for w in model.weights if w.GetNameScope() == namescope] |
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|
| def iter(model, blob_out, **kwargs): |
| if 'device_option' in kwargs: |
| del kwargs['device_option'] |
| model.param_init_net.ConstantFill( |
| [], |
| blob_out, |
| shape=[1], |
| value=0, |
| dtype=core.DataType.INT64, |
| device_option=core.DeviceOption(caffe2_pb2.CPU, 0), |
| **kwargs |
| ) |
| return model.net.Iter(blob_out, blob_out, **kwargs) |
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| def accuracy(model, blob_in, blob_out, **kwargs): |
| dev = kwargs['device_option'] if 'device_option' in kwargs \ |
| else scope.CurrentDeviceScope() |
| is_cpu = dev is None or dev.device_type == caffe2_pb2.CPU |
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| |
| if not is_cpu and 'top_k' in kwargs and kwargs['top_k'] > 1: |
| pred_host = model.net.CopyGPUToCPU(blob_in[0], blob_in[0] + "_host") |
| label_host = model.net.CopyGPUToCPU(blob_in[1], blob_in[1] + "_host") |
|
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| |
| model.net.Accuracy( |
| [pred_host, label_host], |
| blob_out, |
| device_option=core.DeviceOption(caffe2_pb2.CPU, 0), |
| **kwargs |
| ) |
| else: |
| model.net.Accuracy(blob_in, blob_out) |
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|
| def add_weight_decay(model, weight_decay): |
| """Adds a decay to weights in the model. |
| |
| This is a form of L2 regularization. |
| |
| Args: |
| weight_decay: strength of the regularization |
| """ |
| if weight_decay <= 0.0: |
| return |
| wd = model.param_init_net.ConstantFill( |
| [], 'wd', shape=[1], value=weight_decay |
| ) |
| ONE = model.param_init_net.ConstantFill([], "ONE", shape=[1], value=1.0) |
| for param in _get_weights(model): |
| |
| grad = model.param_to_grad[param] |
| model.net.WeightedSum( |
| [grad, ONE, param, wd], |
| grad, |
| ) |
|
|
