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Enabling a Fusion Pattern

According to Registering a Fusion Pattern:

  • A general pattern is enabled by default and cannot be manually disabled.
  • A non-general pattern is disabled by default. You can enable a non-general fusion pattern as required.
    Table 1 Enabling a non-general fusion pattern

    Scenario

    Method

    TensorFlow model conversion using ATC for offline inference

    Include the enable_scope_fusion_passes option to set the fusion pattern (or fusion patterns separated by commas) to take effect.

    --enable_scope_fusion_passes = DecodeBboxV2ScopeFusionPass

    TensorFlow model parsing for offline inference

    Parse a TensorFlow model by using the aclgrphParseTensorFlow call.

    Set ENABLE_SCOPE_FUSION_PASSES to the fusion pattern (or fusion patterns separated by commas) to take effect.

    {ge::AscendString(ge::ir_option::ENABLE_SCOPE_FUSION_PASSES), ge::AscendString("DecodeBboxV2ScopeFusionPass")},

    Training or online inference within the TensorFlow framework

    Set enable_scope_fusion_passes to the fusion pattern (or fusion patterns separated by commas) to take effect within the TensorFlow framework.

    import tensorflow as tf
from npu_bridge.estimator import npu_ops
from tensorflow.core.protobuf.rewriter_config_pb2 import RewriterConfig

config = tf.ConfigProto()
custom_op = config.graph_options.rewrite_options.custom_optimizers.add()
custom_op.name = "NpuOptimizer"
custom_op.parameter_map["use_off_line"].b = True
custom_op.parameter_map["enable_scope_fusion_passes"].s = tf.compat.as_bytes("DecodeBboxV2ScopeFusionPass")
config.graph_options.rewrite_options.remapping = RewriterConfig.OFF

with tf.Session(config=config) as sess:
  sess.run(xx_name_scope) # xx_name_scope is an example of the fused operator name.