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Fix missing prints

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This commit is contained in:
Matthew Honnibal 2021-10-31 17:06:10 +01:00
parent 385946d743
commit 9d7a4f47ad
1 changed files with 0 additions and 10 deletions
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spacy/ml/tb_framework.py
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@ -214,10 +214,6 @@ def forward(model, docs_moves: Tuple[List[Doc], TransitionSystem], is_train: boo
def _forward_reference(model, docs_moves: Tuple[List[Doc], TransitionSystem], is_train: bool):
"""Slow reference implementation, without the precomputation"""
def debug_predict(*msg):
if not is_train:
pass
#print(*msg)
nF = model.get_dim("nF")
tok2vec = model.get_ref("tok2vec")
lower_pad = model.get_param("lower_pad")
@ -234,9 +230,6 @@ def _forward_reference(model, docs_moves: Tuple[List[Doc], TransitionSystem], is
docs, moves = docs_moves
states = moves.init_batch(docs)
tokvecs, backprop_tok2vec = tok2vec(docs, is_train)
debug_predict("Tokvecs shape", tokvecs.shape)
debug_predict("Tokvecs mean", tokvecs.mean(axis=1))
debug_predict("Tokvecs var", tokvecs.var(axis=1))
all_ids = []
all_which = []
all_statevecs = []
@ -249,7 +242,6 @@ def _forward_reference(model, docs_moves: Tuple[List[Doc], TransitionSystem], is
ids = ids[: len(next_states)]
for i, state in enumerate(next_states):
state.set_context_tokens(ids, i, nF)
debug_predict(ids)
# Sum the state features, add the bias and apply the activation (maxout)
# to create the state vectors.
tokfeats3f = model.ops.alloc3f(ids.shape[0], nF, nI)
@ -257,10 +249,8 @@ def _forward_reference(model, docs_moves: Tuple[List[Doc], TransitionSystem], is
for j in range(nF):
if ids[i, j] == -1:
tokfeats3f[i, j] = lower_pad
debug_predict("Setting tokfeat", i, j, "to pad")
else:
tokfeats3f[i, j] = tokvecs[ids[i, j]]
debug_predict("Setting tokfeat", i, j, "to", ids[i, j])
tokfeats = model.ops.reshape2f(tokfeats3f, tokfeats3f.shape[0], -1)
preacts2f = model.ops.gemm(tokfeats, lower_W, trans2=True)
preacts2f += lower_b