# https://github.com/google-research/tensorflow-coder/blob/master/tf_coder/tf_coder_main.py import streamlit as st from tf_coder.value_search import colab_interface, value_search_settings import io from contextlib import redirect_stdout from streamlit_ace import st_ace st.set_page_config(page_icon='👩‍💻', layout="wide", initial_sidebar_state="collapsed") col1, col2, col3 = st.columns([5, 5, 3]) with col1: st.write('### Inputs') inputs = st_ace(placeholder="The input tensor(s) specified as a dictionary", value="{'rows': [10, 20, 30],\n'cols': [1,2,3,4]}", language="python", theme="solarized_dark") with col2: st.write('### Output') output = st_ace(placeholder="The output tensor", value="[[11, 12, 13, 14],\n[21, 22, 23, 24],\n[31, 32, 33, 34]]", language="python", theme="solarized_dark") with col3: st.write('### Constants') constants = st_ace(placeholder="Optional list of scalar constants", value="[]", language="python", theme="solarized_dark") if any([inputs, output, constants]): i = eval(inputs) o = eval(output) c = eval(constants) description = st.text_input(label="Description", placeholder="An optional natural language description of the operation", value="add two vectors with broadcasting to get a matrix") st.sidebar.header("Settings:") settings_kwargs = dict() settings_kwargs["require_all_inputs_used"] = st.sidebar.checkbox("Require All Inputs", value=True) settings_kwargs["only_minimal_solutions"] = st.sidebar.checkbox("Only Minimal Solutions", value=False) settings_kwargs["max_solutions"] = st.sidebar.slider("Maximum number of solutions", value=1, min_value=1, step=1, max_value=256) settings_kwargs["timeout"] = st.sidebar.slider("Timeout in seconds", value=300, min_value=1, step=10, max_value=300) settings = value_search_settings.from_dict({ 'timeout': settings_kwargs["timeout"], 'only_minimal_solutions': settings_kwargs["only_minimal_solutions"], 'max_solutions': settings_kwargs["max_solutions"], 'require_all_inputs_used': settings_kwargs["require_all_inputs_used"], 'require_one_input_used': not settings_kwargs["require_all_inputs_used"], }) with io.StringIO() as buf, redirect_stdout(buf): constants = [] results = colab_interface.run_value_search_from_colab(i, o, c, description, settings) stdout = buf.getvalue() st.code(stdout, language='bash')