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import requests | |
import json | |
import datetime | |
headers = { | |
'accept': 'application/json', | |
'Accept-Language': 'hi_IN', | |
} | |
now = datetime.datetime.now()¬ | |
date = now.strftime("%d-%m-%Y")¬ |
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name: wandb | |
channels: | |
- pytorch | |
- defaults | |
dependencies: | |
- _libgcc_mutex=0.1=main | |
- asn1crypto=1.2.0=py37_0 | |
- attrs=19.3.0=py_0 | |
- backcall=0.1.0=py37_0 | |
- blas=1.0=mkl |
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0 @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ | |
dataset.name = 'dsprites_full' | |
encoder.encoder_fn = @conv_encoder | |
decoder.decoder_fn = @deconv_decoder | |
model.name = 'beta_vae' | |
vae.beta = 1.0 | |
model.model = @vae() | |
model.random_seed = 0 | |
1 @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ |
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'''Trains a simple convnet on the MNIST dataset. | |
Gets to 99.25% test accuracy after 12 epochs | |
(there is still a lot of margin for parameter tuning). | |
16 seconds per epoch on a GRID K520 GPU. | |
''' | |
from __future__ import print_function | |
import wandb | |
wandb.init() | |
from wandb.keras import WandbCallback |
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'''Trains a simple convnet on the MNIST dataset. | |
Gets to 99.25% test accuracy after 12 epochs | |
(there is still a lot of margin for parameter tuning). | |
16 seconds per epoch on a GRID K520 GPU. | |
''' | |
from __future__ import print_function | |
import wandb | |
wandb.init() | |
from wandb.keras import WandbCallback |
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'''Trains a simple convnet on the MNIST dataset. | |
Gets to 99.25% test accuracy after 12 epochs | |
(there is still a lot of margin for parameter tuning). | |
16 seconds per epoch on a GRID K520 GPU. | |
''' | |
from __future__ import print_function | |
import wandb | |
wandb.init() | |
from wandb.keras import WandbCallback |
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'''Trains a simple convnet on the MNIST dataset. | |
Gets to 99.25% test accuracy after 12 epochs | |
(there is still a lot of margin for parameter tuning). | |
16 seconds per epoch on a GRID K520 GPU. | |
''' | |
from __future__ import print_function | |
import wandb | |
wandb.init() | |
from wandb.keras import WandbCallback |
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from osim.http.client import Client | |
from osim.env import GaitEnv | |
#from osim_http_mrl_client import Client as mrl_client | |
remote_base = 'http://grader.crowdai.org' | |
token = 'your token' | |
client = Client(remote_base) | |
g = GaitEnv(visualize=False) | |
# local = mrl_client() |
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""" | |
semi gradient sarsa control of Mountain Car | |
with function approximation, with tiled features | |
TileCoding -> https://gist.github.com/042bb46cc9143a0c027d021c552300cf | |
""" | |
import numpy as np | |
import gym |
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************* Module delight.gcm_utils | |
E: 40,108: Instance of 'bool' has no 'get' member (but some types could not be inferred) (maybe-no-member) | |
E: 41,108: Instance of 'bool' has no 'get' member (but some types could not be inferred) (maybe-no-member) | |
************* Module delight.gcm | |
E:141,30: Instance of 'bool' has no 'get' member (but some types could not be inferred) (maybe-no-member) | |
E:142,15: Instance of 'bool' has no 'has_key' member (but some types could not be inferred) (maybe-no-member) | |
E:143,32: Instance of 'bool' has no 'get' member (but some types could not be inferred) (maybe-no-member) | |
E:153,34: Instance of 'bool' has no 'get' member (but some types could not be inferred) (maybe-no-member) | |
E:155,19: Instance of 'bool' has no 'has_key' member (but some types could not be inferred) (maybe-no-member) | |
E:156,60: Instance of 'bool' has no 'get' member (but some types could not be inferred) (maybe-no-member) |
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