Fix overflow for div arguments.

[ysiraichi]

This PR fixes the div(Tensor, Scalar) operation implementation.

Problem: consider div(tensor(..., dtype=half), 1_000_000)

• GetIrValueForScalar will attempt to convert the scalar into a tensor of dtype=half
• Fails because 1_000_000 is beyond half max value

Solution: use another type for these mathematical operations

• PyTorch makes use of at::OpMathType trait
• Cast the arguments to that type, and then cast the result back

Affected Benchmarks

• (non-dynamo) Super_SloMo training

cc @miladm @JackCaoG

[vanbasten23]

I wonder what error did you see before this fix.

[ysiraichi]

Traceback (most recent call last): File "xla/benchmarks/experiment_runner.py", line 945, in <module> main() File "xla/benchmarks/experiment_runner.py", line 941, in main runner.run() File "xla/benchmarks/experiment_runner.py", line 61, in run self.run_single_config() File "xla/benchmarks/experiment_runner.py", line 256, in run_single_config metrics, last_output = self.run_once_and_gather_metrics( File "xla/benchmarks/experiment_runner.py", line 345, in run_once_and_gather_metrics output, _ = loop(iter_fn=self._default_iter_fn) File "xla/benchmarks/experiment_runner.py", line 302, in loop output, timing, trace = iter_fn(benchmark_experiment, benchmark_model, File "xla/benchmarks/experiment_runner.py", line 218, in _default_iter_fn output = benchmark_model.model_iter_fn( File "xla/benchmarks/torchbench_model.py", line 411, in train super().train(inputs, collect_full_output=collect_full_output) File "xla/benchmarks/benchmark_model.py", line 160, in train loss.backward() File "torch/_tensor.py", line 523, in backward torch.autograd.backward( File "torch/autograd/__init__.py", line 267, in backward _engine_run_backward( File "torch/autograd/graph.py", line 767, in _engine_run_backward return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass RuntimeError: value cannot be converted to type at::Half without overflow