def eval_iter_callback(tensors, global_vars):
if "all_preds" not in global_vars.keys():
global_vars["all_preds"] = []
if "all_labels" not in global_vars.keys():
global_vars["all_labels"] = []
if "all_subtokens_mask" not in global_vars.keys():
global_vars["all_subtokens_mask"] = []
all_subtokens_mask, all_logits, all_labels = [], [], []
for kv, v in tensors.items():
if kv.startswith('logits'):
for v_tensor in v:
for logit_tensor in v_tensor:
all_logits.append(tensor2list(logit_tensor))
elif kv.startswith('labels'):
for v_tensor in v:
for label_tensor in v_tensor:
all_labels.extend(tensor2list(label_tensor))
elif kv.startswith('subtokens_mask'):
for v_tensor in v:
for subtokens_mask_tensor in v_tensor:
all_subtokens_mask.extend(
tensor2list(subtokens_mask_tensor))
all_preds = list(np.argmax(np.asarray(all_logits), 2).flatten())
global_vars["all_preds"].extend(all_preds)
global_vars["all_labels"].extend(all_labels)
global_vars["all_subtokens_mask"].extend(all_subtokens_mask)
def eval_iter_callback(tensors, global_vars):
if "punct_all_preds" not in global_vars.keys():
global_vars["punct_all_preds"] = []
if "punct_all_labels" not in global_vars.keys():
global_vars["punct_all_labels"] = []
if "capit_all_preds" not in global_vars.keys():
global_vars["capit_all_preds"] = []
if "capit_all_labels" not in global_vars.keys():
global_vars["capit_all_labels"] = []
if "all_subtokens_mask" not in global_vars.keys():
global_vars["all_subtokens_mask"] = []
all_subtokens_mask = []
punct_all_logits, punct_all_labels = [], []
capit_all_logits, capit_all_labels = [], []
for kv, v in tensors.items():
if 'Punctuation' in kv and 'logits' in kv:
for v_tensor in v:
for logit_tensor in v_tensor:
punct_all_logits.append(tensor2list(logit_tensor))
elif kv.startswith('punct_labels'):
for v_tensor in v:
for label_tensor in v_tensor:
punct_all_labels.extend(tensor2list(label_tensor))
elif 'Capitalization' in kv and 'logits' in kv:
for v_tensor in v:
for logit_tensor in v_tensor:
capit_all_logits.append(tensor2list(logit_tensor))
elif kv.startswith('capit_labels'):
for v_tensor in v:
for label_tensor in v_tensor:
capit_all_labels.extend(tensor2list(label_tensor))
elif kv.startswith('subtokens_mask'):
for v_tensor in v:
for subtokens_mask_tensor in v_tensor:
all_subtokens_mask.extend(
tensor2list(subtokens_mask_tensor))
punct_all_preds = \
list(np.argmax(np.asarray(punct_all_logits), 2).flatten())
global_vars["punct_all_preds"].extend(punct_all_preds)
global_vars["punct_all_labels"].extend(punct_all_labels)
capit_all_preds = \
list(np.argmax(np.asarray(capit_all_logits), 2).flatten())
global_vars["capit_all_preds"].extend(capit_all_preds)
global_vars["capit_all_labels"].extend(capit_all_labels)
global_vars["all_subtokens_mask"].extend(all_subtokens_mask)