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gautamborad/check_print_format.py

Last active June 15, 2021 17:50
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Eager vs TorchScript print comparison for tensors with all possible DTypes from range 1.e-15 to 1.e+15
Raw
check_print_format.py
import torch
from typing import Any
def f(a : Any):
print(a)
return (isinstance(a, torch.Tensor))
m = torch.jit.script(f)
def pr(ts):
print("Eager:"); f(ts)
print("TS:"); m(ts)
multipliers = [10 ** n for n in range(-15, 15, 5)]
for dt in torch.testing.get_all_fp_dtypes():
o = torch.tensor([[1., -2., 3.]])
for i in multipliers:
print(f"====== type:{dt}, multiplier:{i:.2e} Start =====")
pr(o*i)
print(f"====== End =====")
for dt in torch.testing.get_all_int_dtypes():
o = torch.tensor([[1, -2, 3]])
for i in multipliers:
print(f"====== type:{dt}, multiplier:{i:.2e} Start =====")
pr(o*i)
print(f"====== End =====")
for dt in torch.testing.get_all_complex_dtypes():
o = torch.tensor([3+5j, 4+4j])
for i in multipliers:
print(f"====== type:{dt}, multiplier:{i:.2e} Start =====")
pr(o*i)
print(f"====== End =====")
Raw
grepped_output_for_better_comparison
% python check_print_format.py | grep tensor
# First line is Eager and Second is TorchScript
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1., -2., 3.]])
tensor([[ 1., -2., 3.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1., -2., 3.]])
tensor([[ 1., -2., 3.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1., -2., 3.]])
tensor([[ 1., -2., 3.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1., -2., 3.]])
tensor([[ 1., -2., 3.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 100000., -200000., 300000.]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1, -2, 3]])
tensor([[ 1, -2, 3]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 10000000000, -20000000000, 30000000000]])
tensor([[ 1e+10, -2e+10, 3e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1, -2, 3]])
tensor([[ 1, -2, 3]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 10000000000, -20000000000, 30000000000]])
tensor([[ 1e+10, -2e+10, 3e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1, -2, 3]])
tensor([[ 1, -2, 3]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 10000000000, -20000000000, 30000000000]])
tensor([[ 1e+10, -2e+10, 3e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1, -2, 3]])
tensor([[ 1, -2, 3]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 10000000000, -20000000000, 30000000000]])
tensor([[ 1e+10, -2e+10, 3e+10]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
tensor([[ 1, -2, 3]])
tensor([[ 1, -2, 3]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 100000, -200000, 300000]])
tensor([[ 10000000000, -20000000000, 30000000000]])
tensor([[ 1e+10, -2e+10, 3e+10]])
tensor([3.0000e-15+5.0000e-15j, 4.0000e-15+4.0000e-15j])
tensor([3e-15, 4e-15])
tensor([3.0000e-10+5.0000e-10j, 4.0000e-10+4.0000e-10j])
tensor([3e-10, 4e-10])
tensor([3.0000e-05+5.0000e-05j, 4.0000e-05+4.0000e-05j])
tensor([3e-05, 4e-05])
tensor([3.+5.j, 4.+4.j])
tensor([3, 4])
tensor([300000.+500000.j, 400000.+400000.j])
tensor([300000, 400000])
tensor([3.0000e+10+5.0000e+10j, 4.0000e+10+4.0000e+10j])
tensor([3e+10, 4e+10])
tensor([3.0000e-15+5.0000e-15j, 4.0000e-15+4.0000e-15j])
tensor([3e-15, 4e-15])
tensor([3.0000e-10+5.0000e-10j, 4.0000e-10+4.0000e-10j])
tensor([3e-10, 4e-10])
tensor([3.0000e-05+5.0000e-05j, 4.0000e-05+4.0000e-05j])
tensor([3e-05, 4e-05])
tensor([3.+5.j, 4.+4.j])
tensor([3, 4])
tensor([300000.+500000.j, 400000.+400000.j])
tensor([300000, 400000])
tensor([3.0000e+10+5.0000e+10j, 4.0000e+10+4.0000e+10j])
tensor([3e+10, 4e+10])
Raw
raw_script_output
% python check_print_format.py
====== type:torch.float32, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float32, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float32, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float32, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1., -2., 3.]])
TS:
tensor([[ 1., -2., 3.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float32, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000., -200000., 300000.]])
TS:
tensor([[ 100000., -200000., 300000.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float32, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
TS:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float64, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float64, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float64, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float64, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1., -2., 3.]])
TS:
tensor([[ 1., -2., 3.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float64, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000., -200000., 300000.]])
TS:
tensor([[ 100000., -200000., 300000.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float64, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
TS:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float16, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float16, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float16, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float16, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1., -2., 3.]])
TS:
tensor([[ 1., -2., 3.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float16, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000., -200000., 300000.]])
TS:
tensor([[ 100000., -200000., 300000.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.float16, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
TS:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.bfloat16, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.bfloat16, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.bfloat16, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.bfloat16, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1., -2., 3.]])
TS:
tensor([[ 1., -2., 3.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.bfloat16, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000., -200000., 300000.]])
TS:
tensor([[ 100000., -200000., 300000.]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.bfloat16, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
TS:
tensor([[ 1.0000e+10, -2.0000e+10, 3.0000e+10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.uint8, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.uint8, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.uint8, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.uint8, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1, -2, 3]])
TS:
tensor([[ 1, -2, 3]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.uint8, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000, -200000, 300000]])
TS:
tensor([[ 100000, -200000, 300000]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.uint8, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 10000000000, -20000000000, 30000000000]])
TS:
tensor([[ 1e+10, -2e+10, 3e+10]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int8, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int8, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int8, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int8, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1, -2, 3]])
TS:
tensor([[ 1, -2, 3]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int8, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000, -200000, 300000]])
TS:
tensor([[ 100000, -200000, 300000]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int8, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 10000000000, -20000000000, 30000000000]])
TS:
tensor([[ 1e+10, -2e+10, 3e+10]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int16, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int16, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int16, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int16, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1, -2, 3]])
TS:
tensor([[ 1, -2, 3]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int16, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000, -200000, 300000]])
TS:
tensor([[ 100000, -200000, 300000]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int16, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 10000000000, -20000000000, 30000000000]])
TS:
tensor([[ 1e+10, -2e+10, 3e+10]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int32, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int32, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int32, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int32, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1, -2, 3]])
TS:
tensor([[ 1, -2, 3]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int32, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000, -200000, 300000]])
TS:
tensor([[ 100000, -200000, 300000]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int32, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 10000000000, -20000000000, 30000000000]])
TS:
tensor([[ 1e+10, -2e+10, 3e+10]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int64, multiplier:1.00e-15 Start =====
Eager:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
TS:
tensor([[ 1.0000e-15, -2.0000e-15, 3.0000e-15]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int64, multiplier:1.00e-10 Start =====
Eager:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
TS:
tensor([[ 1.0000e-10, -2.0000e-10, 3.0000e-10]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int64, multiplier:1.00e-05 Start =====
Eager:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
TS:
tensor([[ 1.0000e-05, -2.0000e-05, 3.0000e-05]])
[ CPUFloatType{1,3} ]
====== End =====
====== type:torch.int64, multiplier:1.00e+00 Start =====
Eager:
tensor([[ 1, -2, 3]])
TS:
tensor([[ 1, -2, 3]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int64, multiplier:1.00e+05 Start =====
Eager:
tensor([[ 100000, -200000, 300000]])
TS:
tensor([[ 100000, -200000, 300000]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.int64, multiplier:1.00e+10 Start =====
Eager:
tensor([[ 10000000000, -20000000000, 30000000000]])
TS:
tensor([[ 1e+10, -2e+10, 3e+10]])
[ CPULongType{1,3} ]
====== End =====
====== type:torch.complex64, multiplier:1.00e-15 Start =====
Eager:
tensor([3.0000e-15+5.0000e-15j, 4.0000e-15+4.0000e-15j])
TS:
tensor([3e-15, 4e-15])
[ CPUComplexFloatType{2} ]
test/check_print_format.py:12: UserWarning: Casting complex values to real discards the imaginary part (Triggered internally at ../aten/src/ATen/native/Copy.cpp:240.)
print("TS:"); m(ts)
====== End =====
====== type:torch.complex64, multiplier:1.00e-10 Start =====
Eager:
tensor([3.0000e-10+5.0000e-10j, 4.0000e-10+4.0000e-10j])
TS:
tensor([3e-10, 4e-10])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex64, multiplier:1.00e-05 Start =====
Eager:
tensor([3.0000e-05+5.0000e-05j, 4.0000e-05+4.0000e-05j])
TS:
tensor([3e-05, 4e-05])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex64, multiplier:1.00e+00 Start =====
Eager:
tensor([3.+5.j, 4.+4.j])
TS:
tensor([3, 4])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex64, multiplier:1.00e+05 Start =====
Eager:
tensor([300000.+500000.j, 400000.+400000.j])
TS:
tensor([300000, 400000])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex64, multiplier:1.00e+10 Start =====
Eager:
tensor([3.0000e+10+5.0000e+10j, 4.0000e+10+4.0000e+10j])
TS:
tensor([3e+10, 4e+10])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex128, multiplier:1.00e-15 Start =====
Eager:
tensor([3.0000e-15+5.0000e-15j, 4.0000e-15+4.0000e-15j])
TS:
tensor([3e-15, 4e-15])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex128, multiplier:1.00e-10 Start =====
Eager:
tensor([3.0000e-10+5.0000e-10j, 4.0000e-10+4.0000e-10j])
TS:
tensor([3e-10, 4e-10])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex128, multiplier:1.00e-05 Start =====
Eager:
tensor([3.0000e-05+5.0000e-05j, 4.0000e-05+4.0000e-05j])
TS:
tensor([3e-05, 4e-05])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex128, multiplier:1.00e+00 Start =====
Eager:
tensor([3.+5.j, 4.+4.j])
TS:
tensor([3, 4])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex128, multiplier:1.00e+05 Start =====
Eager:
tensor([300000.+500000.j, 400000.+400000.j])
TS:
tensor([300000, 400000])
[ CPUComplexFloatType{2} ]
====== End =====
====== type:torch.complex128, multiplier:1.00e+10 Start =====
Eager:
tensor([3.0000e+10+5.0000e+10j, 4.0000e+10+4.0000e+10j])
TS:
tensor([3e+10, 4e+10])
[ CPUComplexFloatType{2} ]
====== End =====
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