CANN : Optimize mul_mat_id quantization

[jjjxp03]

For CANN backend:Currently, mul_mat_id performs a device-to-host copy, which does not support full-image inference.Optimize mul_mat_id quantization by referencing the non-quantized version and removing the device_to_host copy operation.

Verify the correctness of the modification using the existing test tool:
./bin/test-backend-ops test -b CANN0 -o MUL_MAT_ID
Passed the q_8 test. Currently, only q_8 has been implemented and tested. Tensor self is not implemented for DT_INT4; to support q_4, the corresponding type implementation needs to be added.

[TianHao324]

The results of running the above-mentioned modifications on the qwen2.5:0.5b f16 model are as follows.

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llama_perf_sampler_print:    sampling time =     104.30 ms /   421 runs   (    0.25 ms per token,  4036.47 tokens per second)
llama_perf_context_print:        load time =    9360.35 ms
llama_perf_context_print: prompt eval time =      15.28 ms /    21 tokens (    0.73 ms per token,  1374.08 tokens per second)
llama_perf_context_print:        eval time =    4707.41 ms /   399 runs   (   11.80 ms per token,    84.76 tokens per second)
llama_perf_context_print:       total time =    8466.42 ms /   420 tokens
llama_perf_context_print:    graphs reused =        386