Remove internal enforce for IO binding inputs

[kunal-vaishnavi]

Description

This PR removes an internal ORT_ENFORCE when binding torch.tensor inputs using IO binding for end-to-end scripts.

Motivation and Context

In merged exports of PyTorch models to ONNX, each past key and past value in the past KV cache has an input shape of (batch_size, num_heads, past_sequence_length, head_size). In the first pass through the model to process the prompt, past_sequence_length = 0. Therefore, each of these inputs is of shape (batch_size, num_heads, 0, head_size). In subsequent passes, past_sequence_length > 0.

When binding a torch.tensor of shape (batch_size, num_heads, 0, head_size) with io_binding.bind_input, the tensor's data_ptr() must be passed. For a torch.tensor of this shape, its data_ptr() returns 0. Because it returns 0, the existing ORT_ENFORCE is therefore false and an error is raised. By removing the internal ORT_ENFORCE, no error is raised and the model runs successfully.

LLaMA-2 Example:

Input Name	Input Size	Device	Device ID	Torch Dtype	data_ptr()
input_ids	torch.Size([1, 11])	cuda	7	torch.int64	140639561842688
attention_mask	torch.Size([1, 11])	cuda	7	torch.int64	140639561843200
position_ids	torch.Size([1, 11])	cuda	7	torch.int64	140639561844224
past_key_values.0.key	torch.Size([1, 32, 0, 128])	cuda	7	torch.float32	0
past_key_values.0.value	torch.Size([1, 32, 0, 128])	cuda	7	torch.float32	0
...	...	...	...	...	...