tbsm_data_pytorch.py [149:156]:
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        time = np.arange(self.ts_length + 1, dtype=np.int32) / (self.ts_length + 1)
        # time = np.ones(self.ts_length + 1, dtype=np.int32)

        users = np.zeros((self.total_out, self.ts_length + 1), dtype="i4")  # 4 byte int
        items = np.zeros((self.total_out, self.ts_length + 1), dtype="i4")  # 4 byte int
        cats = np.zeros((self.total_out, self.ts_length + 1), dtype="i4")  # 4 byte int
        times = np.zeros((self.total_out, self.ts_length + 1), dtype=np.float)
        y = np.zeros(self.total_out, dtype="i4")  # 4 byte int
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tbsm_data_pytorch.py [274:280]:
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        time = np.arange(self.ts_length + 1, dtype=np.int32) / (self.ts_length + 1)

        users = np.zeros((self.total_out, self.ts_length + 1), dtype="i4")  # 4 byte int
        items = np.zeros((self.total_out, self.ts_length + 1), dtype="i4")  # 4 byte int
        cats = np.zeros((self.total_out, self.ts_length + 1), dtype="i4")  # 4 byte int
        times = np.zeros((self.total_out, self.ts_length + 1), dtype=np.float)
        y = np.zeros(self.total_out, dtype="i4")  # 4 byte int
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