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•
ff77572
1
Parent(s):
5927800
fix inf token ui
Browse files- app_text_classification.py +5 -3
- io_utils.py +0 -2
- text_classification_ui_helpers.py +24 -1
app_text_classification.py
CHANGED
@@ -4,7 +4,6 @@ from io_utils import (
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read_scanners,
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write_scanners,
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read_inference_type,
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-
write_inference_type,
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get_logs_file,
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)
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from wordings import INTRODUCTION_MD, CONFIRM_MAPPING_DETAILS_MD
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@@ -14,6 +13,8 @@ from text_classification_ui_helpers import (
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check_dataset_and_get_split,
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check_model_and_show_prediction,
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write_column_mapping_to_config,
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)
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MAX_LABELS = 20
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@@ -70,7 +71,7 @@ def get_demo(demo):
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run_local = gr.Checkbox(value=True, label="Run in this Space")
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use_inference = read_inference_type(uid) == "hf_inference_api"
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run_inference = gr.Checkbox(value=use_inference, label="Run with Inference API")
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-
inference_token = gr.Textbox(value="", label="HF Token for Inference API", visible=False)
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with gr.Accordion(label="Scanner Advance Config (optional)", open=False):
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selected = read_scanners(uid)
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@@ -106,8 +107,9 @@ def get_demo(demo):
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scanners.change(write_scanners, inputs=[scanners, uid_label])
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run_inference.change(
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gr.on(
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triggers=[label.change for label in column_mappings],
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fn=write_column_mapping_to_config,
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read_scanners,
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write_scanners,
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read_inference_type,
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get_logs_file,
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)
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from wordings import INTRODUCTION_MD, CONFIRM_MAPPING_DETAILS_MD
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check_dataset_and_get_split,
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check_model_and_show_prediction,
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write_column_mapping_to_config,
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+
select_run_mode,
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deselect_run_inference,
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)
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MAX_LABELS = 20
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run_local = gr.Checkbox(value=True, label="Run in this Space")
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use_inference = read_inference_type(uid) == "hf_inference_api"
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run_inference = gr.Checkbox(value=use_inference, label="Run with Inference API")
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+
inference_token = gr.Textbox(value="", label="HF Token for Inference API", visible=False, interactive=True)
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with gr.Accordion(label="Scanner Advance Config (optional)", open=False):
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selected = read_scanners(uid)
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scanners.change(write_scanners, inputs=[scanners, uid_label])
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+
run_inference.change(select_run_mode, inputs=[run_inference, uid_label], outputs=[inference_token, run_local])
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run_local.change(deselect_run_inference, inputs=[run_local], outputs=[inference_token, run_inference])
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gr.on(
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triggers=[label.change for label in column_mappings],
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fn=write_column_mapping_to_config,
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io_utils.py
CHANGED
@@ -64,8 +64,6 @@ def write_inference_type(use_inference, uid):
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# save inference_type to inference_type in yaml
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yaml.dump(config, f, Dumper=Dumper)
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f.close()
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-
return (gr.update(visible=(use_inference == "hf_inference_api")))
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-
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# read column mapping from yaml file
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# save inference_type to inference_type in yaml
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yaml.dump(config, f, Dumper=Dumper)
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f.close()
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# read column mapping from yaml file
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text_classification_ui_helpers.py
CHANGED
@@ -9,7 +9,8 @@ import gradio as gr
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from transformers.pipelines import TextClassificationPipeline
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from io_utils import (get_yaml_path, read_column_mapping, save_job_to_pipe,
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-
write_column_mapping, write_log_to_user_file
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from text_classification import (check_model, get_example_prediction,
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get_labels_and_features_from_dataset)
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from wordings import CONFIRM_MAPPING_DETAILS_FAIL_RAW, MAPPING_STYLED_ERROR_WARNING, CHECK_CONFIG_OR_SPLIT_RAW
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@@ -41,7 +42,29 @@ def check_dataset_and_get_split(dataset_id, dataset_config):
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# gr.Warning(f"Failed to load dataset {dataset_id} with config {dataset_config}: {e}")
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pass
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def write_column_mapping_to_config(
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dataset_id, dataset_config, dataset_split, uid, *labels
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):
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from transformers.pipelines import TextClassificationPipeline
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from io_utils import (get_yaml_path, read_column_mapping, save_job_to_pipe,
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write_column_mapping, write_log_to_user_file,
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write_inference_type)
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from text_classification import (check_model, get_example_prediction,
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get_labels_and_features_from_dataset)
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from wordings import CONFIRM_MAPPING_DETAILS_FAIL_RAW, MAPPING_STYLED_ERROR_WARNING, CHECK_CONFIG_OR_SPLIT_RAW
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# gr.Warning(f"Failed to load dataset {dataset_id} with config {dataset_config}: {e}")
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pass
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+
def select_run_mode(run_inf, uid):
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write_inference_type(run_inf, uid)
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if run_inf:
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return (
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gr.update(visible=True),
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gr.update(value=False))
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else:
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return (
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gr.update(visible=False),
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gr.update(value=True))
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def deselect_run_inference(run_local):
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if run_local:
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return (
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gr.update(visible=False),
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gr.update(value=False)
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)
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else:
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return (
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gr.update(visible=True),
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gr.update(value=True)
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)
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+
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def write_column_mapping_to_config(
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dataset_id, dataset_config, dataset_split, uid, *labels
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):
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