adding code and simple tests

README.md

 # Fast Word2Vec TF
 
 Fast implementation of Word2Vec in Tensorflow
+
+## Run Tests
+
+fast_TF_Word2Vec$python3 -m model.tests.test
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model/__init__.py

+from .core.model import *

model/core/model.py

+import tensorflow as tf
+
+def logp(x,y,embedx,embedy,device='/device:GPU:0'):
+  with tf.device(device):
+    # embeded vectors: x is central and y is context
+    y_embed = tf.gather(embedy,y) # (N_BATCH,N_DIM)
+    x_embed = tf.gather(embedx,x) # (N_BATCH,N_DIM)
+
+    # logprob of (y,x) and of (x,)
+    yx_logp = tf.squeeze( tf.matmul(tf.expand_dims(x_embed,1),tf.expand_dims(y_embed,-1))  ) # (N_BATCH,)
+    x_logp = tf.matmul(embedy,tf.transpose(x_embed)) # (N_WORDS,N_BATCH)
+    x_logp = tf.reduce_logsumexp(x_logp,axis=0) # (N_BATCH,)
+
+    # logprob of (y|x)
+    y_x_logp = yx_logp - x_logp # (N_BATCH,1)
+    logp = tf.reduce_mean(y_x_logp)
+    return logp
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model/tests/test.py

+import unittest
+from ..core.model import *
+
+class TestTensorflowSetup(unittest.TestCase):
+
+  def test_version2x(self):
+    self.assertTrue(tf.version.VERSION.startswith('2'))
+
+if __name__ == '__main__':
+    unittest.main()