Spaces:
Running
Running
embedding via /encode endpoint
Browse files- __pycache__/app.cpython-38.pyc +0 -0
- __pycache__/library.cpython-38.pyc +0 -0
- __pycache__/registration.cpython-38.pyc +0 -0
- app.py +24 -3
- out.txt +0 -10
- requirements.txt +1 -0
- scripts/update_valdata.py +2 -1
- test.ipynb +63 -22
- update.txt +0 -1
- update_valdata.py +0 -34
__pycache__/app.cpython-38.pyc
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__pycache__/library.cpython-38.pyc
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__pycache__/registration.cpython-38.pyc
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app.py
CHANGED
@@ -1,13 +1,34 @@
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from flask import Flask,request,render_template,send_file
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import os
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app=Flask(__name__)
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MESSAGED={'title':'Script Server',
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'messageL':['script in "script" parameter or field of json input to /run will be run']}
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@app.route("/file/<string:filename>")
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def
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return send_file(filename)
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@app.route('/run',methods=['GET','POST'])
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def run_script():
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from flask import Flask,request,render_template,send_file,jsonify
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import os
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from transformers import AutoTokenizer, AutoModel
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app=Flask(__name__)
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MESSAGED={'title':'Script Server',
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'messageL':['script in "script" parameter or field of json input to /run will be run']}
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tokenizer = AutoTokenizer.from_pretrained('allenai/specter')
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encoder = AutoModel.from_pretrained('allenai/specter')
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@app.route('/encode',methods=['GET','POST'])
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def encode():
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print(request)
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if request.method=='GET':
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text=request.args.get('text')
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elif request.method=='POST':
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data=request.get_json()
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if 'text' in data: text=data["text"]
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if text=='' or text is None: return -1
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inputs = tokenizer(text, padding=True, truncation=True,
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return_tensors="pt", max_length=512)
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result = encoder(**inputs)
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embeddings = result.last_hidden_state[:, 0, :]
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emb_array = embeddings.detach().numpy()
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embedding=emb_array.tolist()
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return jsonify({'embedding': embedding})
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@app.route("/file/<string:filename>")
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def return_file(filename):
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return send_file('./data/'+filename)
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@app.route('/run',methods=['GET','POST'])
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def run_script():
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out.txt
CHANGED
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total 56
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8 -rw-r--r-- 1 a112956 staff 621 Nov 13 15:08 README.md
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0 drwxr-xr-x 5 a112956 staff 160 Nov 13 15:07 __pycache__
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8 -rw-r--r--@ 1 a112956 staff 1208 Nov 13 16:00 app.py
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0 drwxr-xr-x 2 a112956 staff 64 Nov 13 15:15 flagged
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0 -rw-r--r-- 1 a112956 staff 0 Nov 13 16:02 out.txt
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8 -rw-r--r-- 1 a112956 staff 22 Nov 13 15:21 requirements.txt
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0 drwxr-xr-x 3 a112956 staff 96 Nov 13 15:19 scripts
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24 -rw-r--r-- 1 a112956 staff 9239 Nov 13 15:56 test.ipynb
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8 -rw-r--r-- 1 a112956 staff 12 Nov 13 15:08 update.txt
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requirements.txt
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anvil_uplink
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numerapi
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flask
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anvil_uplink
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numerapi
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flask
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transformers
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scripts/update_valdata.py
CHANGED
@@ -25,10 +25,11 @@ validation_data=pd.read_parquet(data_path+"validation_int8.parquet")
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recent_eras=list(validation_data.loc[validation_data['data_type']=='validation']['era'].unique()[-2:])
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validation_subset=validation_data[validation_data['era'].isin(recent_eras)]
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validation_subset.to_parquet(data_path+"validation_subset_int8.parquet",index=False)
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# In[ ]:
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print("Now please copy the file to server via: scp ../../data/validation_subset_int8.parquet gms@gms1:/home/gms/numerai/data/.")
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recent_eras=list(validation_data.loc[validation_data['data_type']=='validation']['era'].unique()[-2:])
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validation_subset=validation_data[validation_data['era'].isin(recent_eras)]
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validation_subset.to_parquet(data_path+"validation_subset_int8.parquet",index=False)
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# napi.download_dataset('v4.2/live_int8.parquet',data_path+'live_int8.parquet')
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# In[ ]:
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# print("Now please copy the file to server via: scp ../../data/validation_subset_int8.parquet gms@gms1:/home/gms/numerai/data/.")
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test.ipynb
CHANGED
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"cells": [
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {
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"tags": []
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},
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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"headers = {'Content-Type': 'application/json'}\n",
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"# url='http://127.0.0.1:5000/run'\n",
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"url='https://huggingface.co/spaces/gmshroff/gmserver'\n",
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"
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]
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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-
"
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]
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [],
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"source": [
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"response.
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]
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},
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"
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]
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"
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]
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},
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.
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}
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},
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"nbformat": 4,
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"cells": [
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{
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"cell_type": "code",
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+
"execution_count": null,
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"metadata": {
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"tags": []
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},
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"metadata": {},
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"outputs": [],
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"source": [
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"def encode(text,server='local'):\n",
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" headers = {'Content-Type': 'application/json'}\n",
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" if server=='local': url='http://127.0.0.1:7860/encode'\n",
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" elif server=='hf': url='https://huggingface.co/spaces/gmshroff/gmserver'\n",
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" body={'text':text}\n",
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" response=requests.post(url=url,data=json.dumps(body),headers = {'Content-Type': 'application/json'})\n",
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" return json.loads(response.content)['embedding'][0]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"headers = {'Content-Type': 'application/json'}\n",
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"# url='http://127.0.0.1:5000/run'\n",
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"# url='https://huggingface.co/spaces/gmshroff/gmserver'\n",
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"# url='http://127.0.0.1:7860/run'\n",
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"# body={\"script\":\"python update_valdata.py\"}\n",
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"# body={\"script\":\"pwd\"}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 32,
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"metadata": {},
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"outputs": [],
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"source": [
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"url='http://127.0.0.1:7860/encode'\n",
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"body={'text':'I am very good'}\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [],
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"source": [
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"response=requests.post(url=url,data=json.dumps(body),headers = {'Content-Type': 'application/json'})\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<Response [200]>\n"
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]
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}
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],
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"source": [
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"print(response)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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0.57063889503479, 0.06410922110080719, 0.7918137311935425, 0.16293446719646454, -0.1023562029004097, -0.2594066560268402, -0.37953126430511475, 0.36549240350723267, 0.3395199179649353, -0.4856763184070587, -0.3732529282569885, -0.9458137154579163, -0.03560802713036537, 0.09210842102766037, -0.3790932893753052, 0.472409188747406, -0.3025752305984497, 0.10647442936897278, 0.1691814363002777, 0.6113191843032837, 0.9262945652008057, 0.2380715161561966, -0.22122859954833984, -0.06210768222808838, 0.30379608273506165, 0.16581280529499054, -0.05275825783610344, -0.2700578570365906, 0.19631600379943848, -0.8459869027137756, -0.09436513483524323, 0.04790949821472168, -0.1868971288204193, -0.7478898167610168, -0.3465505838394165, -0.9422973394393921, 0.48073846101760864, -0.3396507501602173, -0.4986068308353424, 0.08935505151748657, 0.49811556935310364, 1.304567813873291, -0.26231247186660767, -0.014945432543754578, 0.15545004606246948, -0.30702072381973267, 0.3312910199165344, 1.3234797716140747, 0.25626271963119507, 0.3258507251739502, 0.4615495800971985, 0.2508990466594696, 0.08660449832677841, 1.370755672454834]]\n"
|
92 |
+
]
|
93 |
+
}
|
94 |
+
],
|
95 |
+
"source": [
|
96 |
+
"print(json.loads(response.content)['embedding'])"
|
97 |
+
]
|
98 |
+
},
|
99 |
+
{
|
100 |
+
"cell_type": "code",
|
101 |
+
"execution_count": null,
|
102 |
+
"metadata": {
|
103 |
+
"tags": []
|
104 |
+
},
|
105 |
+
"outputs": [],
|
106 |
+
"source": [
|
107 |
+
"urlretrieve(url='http://127.0.0.1:7860/file/data.csv',filename='./returned_file.csv')"
|
108 |
]
|
109 |
},
|
110 |
{
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|
133 |
"name": "python",
|
134 |
"nbconvert_exporter": "python",
|
135 |
"pygments_lexer": "ipython3",
|
136 |
+
"version": "3.10.13"
|
137 |
}
|
138 |
},
|
139 |
"nbformat": 4,
|
update.txt
DELETED
@@ -1 +0,0 @@
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-
Nov 12 2023
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update_valdata.py
DELETED
@@ -1,34 +0,0 @@
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1 |
-
#!/usr/bin/env python
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2 |
-
# coding: utf-8
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3 |
-
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4 |
-
# In[ ]:
|
5 |
-
|
6 |
-
|
7 |
-
from numerapi import NumerAPI
|
8 |
-
import os
|
9 |
-
import pandas as pd
|
10 |
-
import numpy as np
|
11 |
-
|
12 |
-
|
13 |
-
# In[ ]:
|
14 |
-
|
15 |
-
|
16 |
-
napi = NumerAPI()
|
17 |
-
data_path='./data/'
|
18 |
-
|
19 |
-
|
20 |
-
# In[ ]:
|
21 |
-
|
22 |
-
|
23 |
-
napi.download_dataset("v4.2/validation_int8.parquet", data_path+"validation_int8.parquet")
|
24 |
-
validation_data=pd.read_parquet(data_path+"validation_int8.parquet")
|
25 |
-
recent_eras=list(validation_data.loc[validation_data['data_type']=='validation']['era'].unique()[-2:])
|
26 |
-
validation_subset=validation_data[validation_data['era'].isin(recent_eras)]
|
27 |
-
validation_subset.to_parquet(data_path+"validation_subset_int8.parquet",index=False)
|
28 |
-
|
29 |
-
|
30 |
-
# In[ ]:
|
31 |
-
|
32 |
-
|
33 |
-
print("Now please copy the file to server via: scp ../../data/validation_subset_int8.parquet gms@gms1:/home/gms/numerai/data/.")
|
34 |
-
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