jax support added/multiinput
This commit is contained in:
David Brazda
@ -59,7 +59,7 @@ Jinja2==3.1.2
|
||||
joblib==1.3.2
|
||||
jsonschema==4.17.3
|
||||
jupyterlab-widgets==3.0.9
|
||||
keras==2.15.0
|
||||
keras
|
||||
kiwisolver==1.4.4
|
||||
libclang==16.0.6
|
||||
llvmlite==0.39.1
|
||||
@ -70,7 +70,8 @@ matplotlib==3.8.2
|
||||
matplotlib-inline==0.1.6
|
||||
mdurl==0.1.2
|
||||
ml-dtypes==0.2.0
|
||||
mlroom @ git+https://github.com/drew2323/mlroom.git@768c88348a0bd24c244a8720c67abb20fcb1403e
|
||||
mlroom @ git+https://github.com/drew2323/mlroom.git
|
||||
keras-tcn @ git+https://github.com/drew2323/keras-tcn.git
|
||||
mplfinance==0.12.10b0
|
||||
msgpack==1.0.4
|
||||
mypy-extensions==1.0.0
|
||||
@ -131,11 +132,6 @@ streamlit==1.20.0
|
||||
structlog==23.1.0
|
||||
TA-Lib==0.4.28
|
||||
tenacity==8.2.2
|
||||
tensorboard==2.15.1
|
||||
tensorboard-data-server==0.7.1
|
||||
tensorflow==2.15.0
|
||||
tensorflow-estimator==2.15.0
|
||||
tensorflow-io-gcs-filesystem==0.34.0
|
||||
termcolor==2.3.0
|
||||
threadpoolctl==3.2.0
|
||||
tinydb==4.7.1
|
||||
|
||||
@ -71,29 +71,66 @@ $(document).ready(function() {
|
||||
});
|
||||
}
|
||||
|
||||
// function downloadModel(modelName) {
|
||||
// $.ajax({
|
||||
// url: '/model/download-model/' + modelName,
|
||||
// type: 'GET',
|
||||
// processData: false,
|
||||
// contentType: false,
|
||||
// responseType: 'blob', // This is important
|
||||
// beforeSend: function (xhr) {
|
||||
// xhr.setRequestHeader('X-API-Key', API_KEY);
|
||||
// },
|
||||
// success: function(data, status, xhr) {
|
||||
// // Get a URL for the blob to download
|
||||
// var blob = new Blob([data], { type: 'application/octet-stream' });
|
||||
// //var blob = new Blob([data], { type: xhr.getResponseHeader('Content-Type') });
|
||||
// var downloadUrl = URL.createObjectURL(blob);
|
||||
// var a = document.createElement('a');
|
||||
// a.href = downloadUrl;
|
||||
// a.download = modelName;
|
||||
// document.body.appendChild(a);
|
||||
// a.click();
|
||||
// // Clean up
|
||||
// window.URL.revokeObjectURL(downloadUrl);
|
||||
// a.remove();
|
||||
// },
|
||||
// error: function(xhr, status, error) {
|
||||
// alert('Error downloading model: ' + error + xhr.responseText + status);
|
||||
// }
|
||||
// });
|
||||
// }
|
||||
|
||||
function downloadModel(modelName) {
|
||||
$.ajax({
|
||||
url: '/model/download-model/' + modelName,
|
||||
type: 'GET',
|
||||
beforeSend: function (xhr) {
|
||||
xhr.setRequestHeader('X-API-Key', API_KEY);
|
||||
},
|
||||
success: function(data, status, xhr) {
|
||||
// Get a URL for the blob to download
|
||||
var blob = new Blob([data], { type: xhr.getResponseHeader('Content-Type') });
|
||||
var downloadUrl = URL.createObjectURL(blob);
|
||||
var a = document.createElement('a');
|
||||
a.href = downloadUrl;
|
||||
a.download = modelName;
|
||||
document.body.appendChild(a);
|
||||
a.click();
|
||||
// Clean up
|
||||
window.URL.revokeObjectURL(downloadUrl);
|
||||
a.remove();
|
||||
},
|
||||
error: function(xhr, status, error) {
|
||||
alert('Error downloading model: ' + error + xhr.responseText + status);
|
||||
fetch('/model/download-model/' + modelName, {
|
||||
method: 'GET', // GET is the default method, but it's good to be explicit
|
||||
headers: {
|
||||
'X-API-Key': API_KEY
|
||||
}
|
||||
})
|
||||
.then(response => {
|
||||
if (response.ok) return response.blob();
|
||||
throw new Error('Network response was not ok.');
|
||||
})
|
||||
.then(blob => {
|
||||
// Check the size of the blob here; it should match the Content-Length from the server
|
||||
console.log('Size of downloaded blob:', blob.size);
|
||||
|
||||
// Create a link element, use it for download, and remove it
|
||||
let url = window.URL.createObjectURL(blob);
|
||||
let a = document.createElement('a');
|
||||
a.style.display = 'none';
|
||||
a.href = url;
|
||||
a.download = modelName;
|
||||
document.body.appendChild(a);
|
||||
a.click();
|
||||
window.setTimeout(() => {
|
||||
document.body.removeChild(a);
|
||||
window.URL.revokeObjectURL(url);
|
||||
}, 100); // Cleanup after a small delay
|
||||
})
|
||||
.catch(error => {
|
||||
console.error('Download error:', error);
|
||||
});
|
||||
}
|
||||
|
||||
|
||||
@ -8,7 +8,7 @@ import numpy as np
|
||||
from collections import defaultdict
|
||||
|
||||
"""
|
||||
Předpokladm, že buď používáme 1) bar+standard indikator 2) cbars indicators - zatim nepodporovano spolecne (jine time rozliseni)
|
||||
|
||||
"""
|
||||
def model(state, params, ind_name):
|
||||
funcName = "model"
|
||||
@ -32,25 +32,28 @@ def model(state, params, ind_name):
|
||||
try:
|
||||
mdl = state.vars.loaded_models[name]
|
||||
|
||||
#Optimalizovano, aby se v kazde iteraci nemusel volat len
|
||||
if state.cache.get(name, {}).get("skip_init", False) is False:
|
||||
if mdl.use_cbars is False:
|
||||
if len(state.bars["close"]) < mdl.input_sequences:
|
||||
return 0, 0
|
||||
else:
|
||||
state.cache[name]["skip_init"] = True
|
||||
state.cache[name]["indicators"] = state.indicators
|
||||
state.cache[name]["bars"] = state.bars if mdl.use_bars else {}
|
||||
#return -2, f"too soon - not enough data for seq {seq=}"
|
||||
else:
|
||||
if len(state.cbar_indicators["time"]) < mdl.input_sequences:
|
||||
return 0, 0
|
||||
else:
|
||||
state.cache[name]["skip_init"] = True
|
||||
state.cache[name]["indicators"] = state.cbar_indicators
|
||||
state.cache[name]["bars"] = state.bars if mdl.use_bars else {}
|
||||
# #Optimalizovano, aby se v kazde iteraci nemusel volat len
|
||||
# if state.cache.get(name, {}).get("skip_init", False) is False:
|
||||
# if mdl.use_cbars is False:
|
||||
# if len(state.bars["close"]) < mdl.input_sequences:
|
||||
# return 0, 0
|
||||
# else:
|
||||
# state.cache[name]["skip_init"] = True
|
||||
# state.cache[name]["indicators"] = state.indicators
|
||||
# state.cache[name]["bars"] = state.bars if mdl.use_bars else {}
|
||||
# #return -2, f"too soon - not enough data for seq {seq=}"
|
||||
# else:
|
||||
# if len(state.cbar_indicators["time"]) < mdl.input_sequences:
|
||||
# return 0, 0
|
||||
# else:
|
||||
# state.cache[name]["skip_init"] = True
|
||||
# state.cache[name]["indicators"] = state.cbar_indicators
|
||||
# state.cache[name]["bars"] = state.bars if mdl.use_bars else {}
|
||||
|
||||
value = mdl.predict(state.cache[name]["bars"], state.cache[name]["indicators"])
|
||||
# value = mdl.predict(state.cache[name]["bars"], state.cache[name]["indicators"])
|
||||
|
||||
value = mdl.predict(state)
|
||||
|
||||
return 0, value
|
||||
except Exception as e:
|
||||
printanyway(str(e)+format_exc())
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
import os
|
||||
os.environ["KERAS_BACKEND"] = "jax"
|
||||
from v2realbot.strategy.base import StrategyState
|
||||
from v2realbot.strategy.StrategyOrderLimitVykladaciNormalizedMYSELL import StrategyOrderLimitVykladaciNormalizedMYSELL
|
||||
from v2realbot.enums.enums import RecordType, StartBarAlign, Mode, Account, Followup
|
||||
@ -15,7 +17,6 @@ import numpy as np
|
||||
#from icecream import install, ic
|
||||
from rich import print as printanyway
|
||||
from threading import Event
|
||||
import os
|
||||
from traceback import format_exc
|
||||
|
||||
def initialize_dynamic_indicators(state):
|
||||
|
||||
Reference in New Issue
Block a user