Yuchen Jin YuchenJin

## relax_demos.ipynb

      
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## resnet_parse.py
from tvm.script import relax as R
from tvm import relax

resnet_mod_text = """
@tvm.script.ir_module
class Module:
    @tir.prim_func
    def batch_norm2(rxplaceholder_5: tir.Buffer[(1, 64, 56, 56), "float32"], rxplaceholder_6: tir.Buffer[(64,), "float32"], rxplaceholder_7: tir.Buffer[(64,), "float32"], rxplaceholder_8: tir.Buffer[(64,), "float32"], rxplaceholder_9: tir.Buffer[(64,), "float32"], T_add_2: tir.Buffer[(1, 64, 56, 56), "float32"], T_multiply_3: tir.Buffer[(64,), "float32"], T_multiply_4: tir.Buffer[(64,), "float32"]) -> None:
        # function attr dict
        tir.func_attr({"global_symbol": "batch_norm2", "tir.noalias": True})

## relax_demo.ipynb

      
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                YuchenJin
                / relax_demo.ipynb
            
            
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              November 20, 2022 19:19
            
          
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	from tvm.script import relax as R
	from tvm import relax

	resnet_mod_text = """
	@tvm.script.ir_module
	class Module:
	@tir.prim_func
	def batch_norm2(rxplaceholder_5: tir.Buffer[(1, 64, 56, 56), "float32"], rxplaceholder_6: tir.Buffer[(64,), "float32"], rxplaceholder_7: tir.Buffer[(64,), "float32"], rxplaceholder_8: tir.Buffer[(64,), "float32"], rxplaceholder_9: tir.Buffer[(64,), "float32"], T_add_2: tir.Buffer[(1, 64, 56, 56), "float32"], T_multiply_3: tir.Buffer[(64,), "float32"], T_multiply_4: tir.Buffer[(64,), "float32"]) -> None:
	# function attr dict
	tir.func_attr({"global_symbol": "batch_norm2", "tir.noalias": True})