🐛 Describe the bug

I meet a crash when using Keras with Pytorch backend and executing the following code.

import os
import re
import torch
import numpy as np
os.environ['KERAS_BACKEND']='torch'
import keras

layer = keras.layers.MaxPooling1D(
    pool_size=2,
    strides=1,
    padding="same",
    data_format="channels_first",
    trainable=True,
    dtype="mixed_float16",
    autocast=True,
)

result_dynamic = layer(
    inputs=np.random.rand(*[3, 5, 4]),
)

The error msg is:

...\torch\nn\functional.py:4552, in pad(input, pad, mode, value)
   4545         if mode == 'replicate':
   4546             # Use slow decomp whose backward will be in terms of index_put.
   4547             # importlib is required because the import cannot be top level
   4548             # (cycle) and cannot be nested (TS doesn't support)
   4549             return importlib.import_module('torch._decomp.decompositions')._replication_pad(
   4550                 input, pad
   4551             )
-> 4552 return torch._C._nn.pad(input, pad, mode, value)

RuntimeError: Exception encountered when calling MaxPooling1D.call().

"replication_pad1d" not implemented for 'Half'

The message is wired since the data is of dtype="mixed_float16" rather than 'Half'.

After reporting this issue to Keras team, the developers of Keras point out that it may be a problem of Pytorch backend, so I report this issue here.

Versions

PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04 LTS (x86_64)
GCC version: (Ubuntu 13.2.0-23ubuntu4) 13.2.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.39

Python version: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:36:39) [GCC 10.4.0] (64-bit runtime)
Python platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Quadro T1000
Nvidia driver version: Could not collect
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 39 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 12
On-line CPU(s) list: 0-11
Vendor ID: GenuineIntel
Model name: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
CPU family: 6
Model: 158
Thread(s) per core: 2
Core(s) per socket: 6
Socket(s): 1
Stepping: 10
BogoMIPS: 5184.01
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology cpuid pni pclmulqdq ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti ssbd ibrs ibpb stibp fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt xsaveopt xsavec xgetbv1 xsaves md_clear flush_l1d arch_capabilities
Hypervisor vendor: Microsoft
Virtualization type: full
L1d cache: 192 KiB (6 instances)
L1i cache: 192 KiB (6 instances)
L2 cache: 1.5 MiB (6 instances)
L3 cache: 12 MiB (1 instance)
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported
Vulnerability L1tf: Mitigation; PTE Inversion
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Retbleed: Mitigation; IBRS
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; IBRS, IBPB conditional, STIBP conditional, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Unknown: Dependent on hypervisor status
Vulnerability Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] optree==0.11.0
[pip3] torch==2.4.0
[pip3] triton==3.0.0
[conda] numpy 1.26.4
[conda] optree 0.11.0
[conda] torch 2.4.0
[conda] triton 3.0.0

cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10