cxx122 opened a new issue, #12569: URL: https://github.com/apache/tvm/issues/12569
``` TENSOR_0 = te.placeholder([], dtype="int8", name="TENSOR_0") TENSOR_1 = te.placeholder([], dtype="int8", name="TENSOR_1") TENSOR_2 = te.compute([5], lambda fcc:te.floordiv(TENSOR_1, TENSOR_0-TENSOR_0), name ="TENSOR_2") ``` ### Expected behavior Check failed: pb->value != 0 (0 vs. 0) : Divide by zero ### Actual behavior ### Numpy behavior  ### Environment Operating System: Ubuntu 18.04, TVM version: tag0.9.0 [d361585] ### Steps to reproduce ``` import os import numpy as np import tvm from tvm import te, auto_scheduler, topi import tvm.testing TENSOR_0 = te.placeholder([], dtype="int8", name="TENSOR_0") TENSOR_1 = te.placeholder([], dtype="int8", name="TENSOR_1") TENSOR_2 = te.compute([5], lambda fcc:te.floordiv(TENSOR_1, TENSOR_0-TENSOR_0), name ="TENSOR_2") s = te.create_schedule(TENSOR_2.op) tensor_list = [TENSOR_0,TENSOR_1,TENSOR_2] dev = tvm.cpu(0) pre_list = [] after_list = [] for tensor in tensor_list: shape = [x.value if 'value' in dir(x) and isinstance(x.value, int) else 1 for x in tensor.shape] params = (5*np.random.uniform(size=shape)+1).astype(tensor.dtype) pre_list.append(tvm.nd.array(params.copy(), dev)) after_list.append(tvm.nd.array(params.copy(), dev)) pre_mod = tvm.lower(s, tensor_list, simple_mode=True) with tvm.transform.PassContext(opt_level=0): f = tvm.build(pre_mod) f(*pre_list) ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
