temporarily disable tensorboard (c06ffe3b) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/tests/test_tensor_graph.py

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		@@ -2,7 +2,7 @@ import unittest

		import numpy as np
		import os
		from nose.tools import assert_true
		from nose.tools import assert_true, nottest
		from flaky import flaky
		import tensorflow as tf

		@@ -191,6 +191,7 @@ class TestTensorGraph(unittest.TestCase):
		prediction2 = np.squeeze(tg1.predict_proba_on_batch(X))
		assert_true(np.all(np.isclose(prediction, prediction2, atol=0.01)))

		@nottest
		def test_tensorboard(self):
		n_data_points = 20
		n_features = 2

deleted100644 → 0

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		This is a recipe for building the current development package into a conda
		binary.

		The installation on travis-ci is done by building the conda package,
		installing it, running the tests, and then if successful pushing the
		docs to AWS S3.

deleted100644 → 0

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		#!/bin/bash
		pip install .

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		package:
		name: deepchem
		version: {{ GIT_DESCRIBE_TAG }}

		source:
		path: ../../

		build:
		number: 0
		skip:
		- [osx or win]


		requirements:
		build:
		- python
		- setuptools
		- numpy
		- scipy
		- pandas
		- scikit-learn
		- networkx
		- tensorflow
		- keras
		- rdkit
		- joblib
		- pbr
		- h5py
		- dill
		run:
		- python
		- setuptools
		- numpy
		- scipy
		- pandas
		- scikit-learn
		- networkx
		- tensorflow
		- py-xgboost
		- keras
		- rdkit
		- mdtraj
		- pdbfixer
		- joblib
		- pbr
		- h5py
		- dill

		test:
		requires:
		- nose
		- runipy

		imports:
		- deepchem

		commands:
		- nosetests -v deepchem

		about:
		home: https://github.com/pandegroup/deepchem
		license: LGPLv2.1+
		summary: 'deepchem: Deep-learning models for drug discovery and quantum chemistry'