Delete deepscreen/gui

deepscreen/gui/test.py

@@ -1,114 +0,0 @@
-from pathlib import Path
-
-import gradio as gr
-
-# Use this in a notebook
-root = Path.cwd()
-
-
-drug_encoder_list = [f.stem for f in root.parent.joinpath("configs/model/drug_encoder").iterdir() if f.suffix == ".yaml"]
-
-drug_featurizer_list = [f.stem for f in root.parent.joinpath("configs/model/drug_featurizer").iterdir() if f.suffix == ".yaml"]
-
-protein_encoder_list = [f.stem for f in root.parent.joinpath("configs/model/protein_encoder").iterdir() if f.suffix == ".yaml"]
-
-protein_featurizer_list = [f.stem for f in root.parent.joinpath("configs/model/protein_featurizer").iterdir() if f.suffix == ".yaml"]
-
-classifier_list = [f.stem for f in root.parent.joinpath("configs/model/classifier").iterdir() if f.suffix == ".yaml"]
-
-preset_list = [f.stem for f in root.parent.joinpath("configs/model/preset").iterdir() if f.suffix == ".yaml"]
-
-
-from typing import Optional
-
-def drug_target_interaction(
-        binary: bool,
-        drug_encoder,
-        drug_featurizer,
-        protein_encoder,
-        protein_featurizer,
-        classifier,
-        preset,) -> Optional[float]:
-
-
-    return 1
-
-def drug_encoder(
-        binary: bool,
-        drug_encoder,
-        drug_featurizer,
-        protein_encoder,
-        protein_featurizer,
-        classifier,
-        preset,):
-
-    return
-
-def protein_encoder(
-        binary: bool,
-        drug_encoder,
-        drug_featurizer,
-        protein_encoder,
-        protein_featurizer,
-        classifier,
-        preset,):
-
-    return
-
-# demo = gr.Interface(
-#     fn=drug_target_interaction,
-#     inputs=[
-#         gr.Radio(["True", "False"]),
-#         gr.Dropdown(drug_encoder_list),
-#         gr.Dropdown(drug_featurizer_list),
-#         gr.Dropdown(protein_encoder_list),
-#         gr.Dropdown(protein_featurizer_list),
-#         gr.Dropdown(classifier_list),
-#         gr.Dropdown(preset_list),
-#     ],
-#     outputs=["number"],
-#     show_error=True,
-#
-# )
-#
-# demo.launch()
-
-
-from omegaconf import DictConfig, OmegaConf
-
-type_to_component_map = {list: gr.Text, int: gr.Number, float: gr.Number}
-
-
-def get_config_choices(config_path: str):
-    return [f.stem for f in Path("../../configs/", config_path).iterdir() if f.suffix == ".yaml"]
-
-
-def create_blocks_from_config(cfg: DictConfig):
-    with gr.Blocks() as blocks:
-        for key, value in cfg.items():
-            if type(value) in [int, float]:
-                component = gr.Number(value=value, label=key, interactive=True)
-            if type(value) in [dict, DictConfig]:
-                with gr.Tab(label=key):
-                    component = create_blocks_from_config(value)
-            else:
-                component = gr.Text(value=value, label=key, interactive=True)
-    return blocks
-
-
-def create_interface_from_config(fn: callable, cfg: DictConfig):
-    inputs = []
-
-    for key, value in OmegaConf.to_object(cfg).items():
-        component = type_to_component_map.get(type(value), gr.Text)
-        inputs.append(component(value=value, label=key, interactive=True))
-
-    interface = gr.Interface(fn=fn, inputs=inputs, outputs="label")
-
-    return interface
-
-
-import hydra
-
-with hydra.initialize(version_base=None, config_path="../../configs/"):
-    cfg = hydra.compose("train")