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trying some stuff

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svlandeg 2020-09-19 19:11:30 +02:00
parent 73ff52b9ec
commit 6db1d5dc0d
1 changed files with 15 additions and 0 deletions
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spacy/cli/debug_model.py
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@ -89,6 +89,7 @@ def debug_model(nlp, model: Model, *, print_settings: Optional[Dict[str, Any]] =
# STEP 1: Initializing the model and printing again # STEP 1: Initializing the model and printing again
X = _get_docs() X = _get_docs()
goldY = _get_output(model.ops) goldY = _get_output(model.ops)
# _set_output_dim(nO=goldY.shape[-1], model=model)
# The output vector might differ from the official type of the output layer # The output vector might differ from the official type of the output layer
with data_validation(False): with data_validation(False):
model.initialize(X=X, Y=goldY) model.initialize(X=X, Y=goldY)
@ -108,6 +109,7 @@ def debug_model(nlp, model: Model, *, print_settings: Optional[Dict[str, Any]] =
if tok2vec: if tok2vec:
tok2vec.predict(X) tok2vec.predict(X)
Y, get_dX = model.begin_update(X) Y, get_dX = model.begin_update(X)
print("get_dX", get_dX)
dY = get_gradient(goldY, Y) dY = get_gradient(goldY, Y)
get_dX(dY) get_dX(dY)
model.finish_update(optimizer) model.finish_update(optimizer)
@ -152,6 +154,10 @@ def _get_output(ops):
return ops.xp.asarray(output) return ops.xp.asarray(output)
def _get_output_old(xp):
return xp.asarray([i + 10 for i, _ in enumerate(_get_docs())], dtype="float32")
def _print_model(model, print_settings): def _print_model(model, print_settings):
layers = print_settings.get("layers", "") layers = print_settings.get("layers", "")
parameters = print_settings.get("parameters", False) parameters = print_settings.get("parameters", False)
@ -200,3 +206,12 @@ def _print_matrix(value):
sample_matrix = sample_matrix[0:5] sample_matrix = sample_matrix[0:5]
result = result + str(sample_matrix) result = result + str(sample_matrix)
return result return result
def _set_output_dim(model, nO):
# the dim inference doesn't always work 100%, we need this hack like we have it in pipe.pyx
if model.has_dim("nO") is None:
model.set_dim("nO", nO)
if model.has_ref("output_layer"):
if model.get_ref("output_layer").has_dim("nO") is None:
model.get_ref("output_layer").set_dim("nO", nO)