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Remove unused methods
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ba22111ff4
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@ -152,30 +152,11 @@ class Pipe:
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return sgd
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def set_output(self, nO):
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# TODO: document this across components?
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if self.model.has_dim("nO") is not False:
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self.model.set_dim("nO", nO)
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if self.model.has_ref("output_layer"):
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self.model.get_ref("output_layer").set_dim("nO", nO)
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def get_gradients(self):
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"""Get non-zero gradients of the model's parameters, as a dictionary
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keyed by the parameter ID. The values are (weights, gradients) tuples.
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"""
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# TODO: How is this used?
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gradients = {}
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queue = [self.model]
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seen = set()
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for node in queue:
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if node.id in seen:
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continue
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seen.add(node.id)
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if hasattr(node, "_mem") and node._mem.gradient.any():
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gradients[node.id] = [node._mem.weights, node._mem.gradient]
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if hasattr(node, "_layers"):
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queue.extend(node._layers)
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return gradients
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def use_params(self, params):
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"""Modify the pipe's model, to use the given parameter values. At the
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end of the context, the original parameters are restored.
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@ -378,23 +378,6 @@ cdef class Parser:
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del tutor
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return losses
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def get_gradients(self):
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"""Get non-zero gradients of the model's parameters, as a dictionary
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keyed by the parameter ID. The values are (weights, gradients) tuples.
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"""
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gradients = {}
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queue = [self.model]
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seen = set()
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for node in queue:
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if node.id in seen:
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continue
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seen.add(node.id)
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if hasattr(node, "_mem") and node._mem.gradient.any():
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gradients[node.id] = [node._mem.weights, node._mem.gradient]
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if hasattr(node, "_layers"):
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queue.extend(node._layers)
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return gradients
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def get_batch_loss(self, states, golds, float[:, ::1] scores, losses):
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cdef StateClass state
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cdef Pool mem = Pool()
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