| import solara |
| import pandas as pd |
| import os |
| import zipfile |
| from ray.tune.registry import register_env |
| from env import Teastore |
| from ray.rllib.algorithms import ppo, sac, dqn |
| from solara.components.file_drop import FileInfo |
| import time |
|
|
| test_plot_data = solara.reactive({'step': [], 'replica': [], 'cpu': [], "load": [], |
| "num_request": [], "response_time": []}) |
| uploaded_algo = solara.reactive(None) |
| error_state = solara.reactive(None) |
| number_of_steps = solara.reactive(10) |
| available_checkpoint_names = solara.reactive([]) |
| selected_checkpoint_name = solara.reactive(None) |
| uploaded_algo_status = solara.reactive(False) |
|
|
|
|
|
|
| @solara.component |
| def status_plot(data): |
| options_replica = { |
| "xAxis": { |
| "type": "category", |
| "data": data["step"], |
| }, |
| "yAxis": { |
| "type": "value", |
| }, |
| "series": [ |
| { |
| "name": "Replica", |
| "data": data['replica'], |
| "type": 'line' |
| }, |
| ], |
| "title": { |
| "text": 'Replica Number', |
| "left": "center" |
| }, |
| "legend": { |
| "orient": 'vertical', |
| "right": 0, |
| |
| |
| "data": ["Replica"] |
| }, |
|
|
|
|
| } |
|
|
| options_cpu= { |
| "xAxis": { |
| "type": "category", |
| "data": data["step"], |
| }, |
| "yAxis": { |
| "type": "value", |
| }, |
| "series": [ |
| { |
| "name": "CPU", |
| "data": data['cpu'], |
| "type": 'line' |
| }, |
| ], |
| "title": { |
| "text": 'CPU Limit', |
| "left": "center" |
| }, |
| "legend": { |
| "orient": 'vertical', |
| "right": 0, |
| |
| |
| "data": ["CPU"] |
| }, |
| } |
| options_load= { |
| "xAxis": { |
| "type": "category", |
| "data": data["step"], |
| }, |
| "yAxis": { |
| "type": "value", |
| }, |
| "series": [ |
| { |
| "name": "Processed req", |
| "data": data['num_request'], |
| "type": 'line' |
| }, |
| { |
| "name": "Load", |
| "data": data['load'], |
| "type": 'line' |
| }, |
|
|
| ], |
| "title": { |
| "text": 'Number of Request (Tps) and Load (Tps)', |
| "left": "center" |
| }, |
| "legend": { |
| "orient": 'vertical', |
| "right": 0, |
| |
| |
| "data": ["Processed req", "Load"] |
| }, |
| } |
| options_response_time= { |
| "xAxis": { |
| "type": "category", |
| "data": data["step"], |
| }, |
| "yAxis": { |
| "type": "value", |
| }, |
| "series": [ |
| { |
| "name": "Response time", |
| "data": data['response_time'], |
| "type": 'line' |
| }, |
| ], |
| "title": { |
| "text": 'Response time (ms)', |
| "left": "center" |
| }, |
| "legend": { |
| "orient": 'vertical', |
| "right": 0, |
| |
| |
| "data": ["Response time"] |
| }, |
| } |
|
|
|
|
|
|
| with solara.GridFixed(columns=1): |
| |
| solara.FigureEcharts(option=options_replica) |
| solara.FigureEcharts(option=options_cpu) |
| |
| |
| solara.FigureEcharts(option=options_load) |
| solara.FigureEcharts(option=options_response_time) |
|
|
|
|
|
|
|
|
| @solara.component |
| def CheckpointDrop(): |
| zip_content, set_zip_content = solara.use_state("") |
| content, set_content = solara.use_state(b"") |
| filename, set_filename = solara.use_state("") |
| size, set_size = solara.use_state(0) |
| extract_path, set_extract_path = solara.use_state("") |
|
|
|
|
| def on_file(f: FileInfo): |
| set_filename(f["name"]) |
| set_size(f["size"]) |
| temp_path = os.path.join(f["name"]) |
| with open(temp_path, "wb") as temp_file: |
| temp_file.write(f["file_obj"].read()) |
|
|
| extracted_folder = os.path.join("extracted_files", os.path.splitext(f["name"])[0]) |
| with zipfile.ZipFile(temp_path, 'r') as zip_ref: |
| zip_ref.extractall(extracted_folder) |
|
|
| set_extract_path(extracted_folder) |
| extracted_files = os.listdir(extracted_folder) |
| set_zip_content("\n".join(extracted_files)) |
|
|
| |
| |
| |
| available_checkpoint_names.set(['denee']) |
|
|
| os.remove(temp_path) |
|
|
|
|
| |
| solara.FileDrop( |
| label="Drag and drop a file here", |
| on_file=on_file, |
| lazy=True, |
| ) |
|
|
| @solara.component |
| def ListAvailableCheckpoints(): |
| list_subfolders_names = [f.name for f in os.scandir("extracted_files") if f.is_dir()] |
| available_checkpoint_names.set(list_subfolders_names) |
|
|
|
|
| def load_agent(): |
| if selected_checkpoint_name.value is None: |
| return None |
|
|
| register_env("teastore", lambda config: Teastore()) |
|
|
| config_dqn = ( |
| dqn.DQNConfig() |
| .environment(env="teastore") |
| .rollouts(num_rollout_workers=1, enable_connectors=False, num_envs_per_worker=1) |
| .resources(num_gpus=0, num_cpus_per_worker=1) |
| .training(train_batch_size=256, model={"fcnet_hiddens": [32, 32]}) |
| ) |
| algo = config_dqn.build() |
| checkpoint_dir = selected_checkpoint_name.value |
| checkpoint_path = os.path.join("extracted_files", checkpoint_dir) |
| algo.restore(checkpoint_path) |
|
|
| |
|
|
| return algo |
|
|
| def start_test(): |
|
|
| env = Teastore() |
| obs, info = env.reset() |
| done = False |
| truncated = False |
| sum_reward = 0 |
| step_list = [] |
| replica_array = [] |
| cpu_array = [] |
| num_request_array = [] |
| load_array = [] |
| response_time_array = [] |
|
|
|
|
|
|
| for i in range(number_of_steps.value): |
| step_list.append(i) |
| replica_array.append(obs[0]) |
| cpu_array.append(obs[1]) |
| load_array.append(env.load) |
| response_time_array.append(env.response_time) |
| num_request_array.append(env.num_request) |
|
|
| action = uploaded_algo.value.compute_single_action(obs, explore=False) |
| next_state, reward, _, _, _ = env.step(action) |
| obs = next_state |
|
|
|
|
| test_plot_data.set( |
| {'step':step_list.copy(), |
| 'replica': replica_array.copy(), |
| 'cpu': cpu_array.copy(), |
| "load": load_array.copy(), |
| "response_time": response_time_array.copy(), |
| "num_request": num_request_array.copy() |
| }) |
| |
|
|
| def load_test(): |
| algo = load_agent() |
| if algo is None: |
| error_state.set('Couldnt load checkpoint') |
| else: |
| uploaded_algo_status.set(True) |
| uploaded_algo.set(algo) |
|
|
|
|
| @solara.component |
| def Page(): |
|
|
|
|
| with solara.Sidebar(): |
| if error_state.value is not None: |
| solara.Error(label=f'{error_state.value}') |
| |
| ListAvailableCheckpoints() |
| solara.Select(label="Choose checkpoint", values=available_checkpoint_names.value, value=selected_checkpoint_name.value, |
| on_value=selected_checkpoint_name.set |
| ) |
| solara.Button(label="Run test", on_click=start_test, disabled=True if uploaded_algo.value is None else False) |
| solara.Button(label="Load agent", on_click=load_test, disabled=True if selected_checkpoint_name.value is None else False) |
| if uploaded_algo_status.value == False: |
| solara.Info("Agent is not uploaded") |
| else: |
| solara.Info("Agent is ready for test") |
| solara.SliderInt(label="choose number of steps", min=1, max=500, value=number_of_steps) |
| |
|
|
| status_plot(test_plot_data.value) |
| |
|
|
| |
|
|
|
|
