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@@ -51,6 +51,7 @@ embeddings are stored in separate files.
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"""
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+from __future__ import print_function
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import argparse
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import glob
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import math
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@@ -163,7 +164,7 @@ def write_embeddings_to_disk(config, model, sess):
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# Row Embedding
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row_vocab_path = config.input_base_path + '/row_vocab.txt'
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row_embedding_output_path = config.output_base_path + '/row_embedding.tsv'
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- print 'Writing row embeddings to:', row_embedding_output_path
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+ print('Writing row embeddings to:', row_embedding_output_path)
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sys.stdout.flush()
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write_embedding_tensor_to_disk(row_vocab_path, row_embedding_output_path,
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sess, model.row_embedding)
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@@ -171,7 +172,7 @@ def write_embeddings_to_disk(config, model, sess):
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# Column Embedding
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col_vocab_path = config.input_base_path + '/col_vocab.txt'
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col_embedding_output_path = config.output_base_path + '/col_embedding.tsv'
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- print 'Writing column embeddings to:', col_embedding_output_path
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+ print('Writing column embeddings to:', col_embedding_output_path)
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sys.stdout.flush()
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write_embedding_tensor_to_disk(col_vocab_path, col_embedding_output_path,
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sess, model.col_embedding)
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@@ -185,7 +186,7 @@ class SwivelModel(object):
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self._config = config
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# Create paths to input data files
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- print 'Reading model from:', config.input_base_path
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+ print('Reading model from:', config.input_base_path)
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sys.stdout.flush()
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count_matrix_files = glob.glob(config.input_base_path + '/shard-*.pb')
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row_sums_path = config.input_base_path + '/row_sums.txt'
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@@ -197,12 +198,12 @@ class SwivelModel(object):
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self.n_rows = len(row_sums)
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self.n_cols = len(col_sums)
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- print 'Matrix dim: (%d,%d) SubMatrix dim: (%d,%d) ' % (
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- self.n_rows, self.n_cols, config.submatrix_rows, config.submatrix_cols)
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+ print('Matrix dim: (%d,%d) SubMatrix dim: (%d,%d) ' % (
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+ self.n_rows, self.n_cols, config.submatrix_rows, config.submatrix_cols))
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sys.stdout.flush()
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self.n_submatrices = (self.n_rows * self.n_cols /
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(config.submatrix_rows * config.submatrix_cols))
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- print 'n_submatrices: %d' % (self.n_submatrices)
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+ print('n_submatrices: %d' % (self.n_submatrices))
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sys.stdout.flush()
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# ===== CREATE VARIABLES ======
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@@ -316,15 +317,15 @@ def main(_):
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t0 = [time.time()]
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def TrainingFn():
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- for _ in range(n_steps_per_thread):
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+ for _ in range(int(n_steps_per_thread)):
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_, global_step = sess.run([model.train_op, model.global_step])
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n_steps_between_status_updates = 100
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if (global_step % n_steps_between_status_updates) == 0:
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elapsed = float(time.time() - t0[0])
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- print '%d/%d submatrices trained (%.1f%%), %.1f submatrices/sec' % (
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+ print('%d/%d submatrices trained (%.1f%%), %.1f submatrices/sec' % (
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global_step, n_submatrices_to_train,
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100.0 * global_step / n_submatrices_to_train,
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- n_steps_between_status_updates / elapsed)
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+ n_steps_between_status_updates / elapsed))
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sys.stdout.flush()
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t0[0] = time.time()
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Chris Waterson