Cross plantform versiongit status !
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@@ -103,7 +103,7 @@ def train(dataset, show_bar=False):
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if i % 100 == 0:
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if i % 1000 == 0:
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test_samples, test_labels = dataset.sample_test_sets(5000)
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test_samples, test_labels = dataset.sample_test_sets(1000)
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acc = sess.run(accuracy, feed_dict={x: test_samples, y_: test_labels})
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bar.set_postfix({"loss": loss_value, "acc": acc})
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@@ -72,13 +72,13 @@ def forward(x, regularizer=None):
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node = pool_shape[1] * pool_shape[2] * pool_shape[3]
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reshaped = tf.reshape(pool2, [-1, node])
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fc1_w = get_weight([node, FC1_OUTPUT_NODES], regularizer)
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fc1_w = tf.nn.dropout(get_weight([node, FC1_OUTPUT_NODES], regularizer), 0.1)
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fc1_b = get_bias([FC1_OUTPUT_NODES])
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fc1 = tf.nn.relu(tf.matmul(reshaped, fc1_w) + fc1_b)
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vars.extend([fc1_w, fc1_b])
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nodes.extend([fc1])
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fc2_w = get_weight([FC1_OUTPUT_NODES, FC2_OUTPUT_NODES], regularizer)
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fc2_w = tf.nn.dropout(get_weight([FC1_OUTPUT_NODES, FC2_OUTPUT_NODES], regularizer), 0.1)
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fc2_b = get_bias([FC2_OUTPUT_NODES])
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fc2 = tf.nn.softmax(tf.matmul(fc1, fc2_w) + fc2_b)
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vars.extend([fc2_w, fc2_b])
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