[webgpu] Apply Flash Attention if sliding window exceeds KV cache length (#25594)

### Description
<!-- Describe your changes. -->
#25372 adds sliding window support for Group Query Attention, disabling
Flash Attention as it's not yet supported.

This PR adds a check for the sliding window and applies Flash Attention
when the window size exceeds the KV cache length or total sequence
length.

### Motivation and Context
See above.

Author: daijh

onnxruntime/contrib_ops/webgpu/bert/group_query_attention.cc

@@ -198,9 +198,12 @@ Status GroupQueryAttention::ComputeInternal(onnxruntime::webgpu::ComputeContext&
   Tensor* present_value = context.Output(2, present_kv_shape);
   parameters.past_present_share_buffer_ = present_key != nullptr && present_value != nullptr && past_key != nullptr && past_value != nullptr && past_key->DataRaw() == present_key->DataRaw() && past_value->DataRaw() == present_value->DataRaw();
 
+  ORT_ENFORCE(parameters.total_sequence_length_ <= parameters.seqlen_present_kv_cache_, "Total sequence length cannot be greater than the existing KV cache length.");
+  // Use a sliding window if the total sequence exceeds the window's length.
+  bool use_sliding_window = (local_window_size_ != -1 && local_window_size_ < parameters.total_sequence_length_);
   if (!do_rotary_ &&
       head_sink == nullptr && !use_smooth_softmax_ &&
-      local_window_size_ == -1 &&
+      !use_sliding_window &&
       CanApplyFlashAttention(attention_bias, present_key, present_value, parameters, context)) {
     return ApplyFlashAttention(query, key, value, attention_bias, output, past_key, present_key, past_value,
                                present_value, parameters, context);