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<div class="section" id="quantization-backend-configuration">
<h1>Quantization Backend Configuration<a class="headerlink" href="#quantization-backend-configuration" title="Permalink to this headline">¶</a></h1>
<p>FX Graph Mode Quantization allows the user to configure various
quantization behaviors of an op in order to match the expectation
of their backend.</p>
<p>In the future, this document will contain a detailed spec of
these configurations.</p>
<div class="section" id="default-values-for-native-configurations">
<h2>Default values for native configurations<a class="headerlink" href="#default-values-for-native-configurations" title="Permalink to this headline">¶</a></h2>
<p>Below is the output of the configuration for quantization of ops
in fbgemm and qnnpack (PyTorch’s default quantized backends).</p>
<p>Results:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>{
'pattern': <class 'torch.nn.modules.pooling.AdaptiveAvgPool1d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <built-in method adaptive_avg_pool1d of type object at 0x7fc9db52bd40>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <class 'torch.nn.modules.pooling.AdaptiveAvgPool2d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <function adaptive_avg_pool2d at 0x7fc98a30ba70>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <class 'torch.nn.modules.pooling.AdaptiveAvgPool3d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <function adaptive_avg_pool3d at 0x7fc98a30b950>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': (<class 'torch.nn.modules.activation.ReLU'>, <built-in function add>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': (<function relu at 0x7fc98a30bef0>, <built-in function add>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': (<built-in method relu of type object at 0x7fc9db52bd40>, <built-in function add>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': <built-in function add>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': (<class 'torch.nn.modules.activation.ReLU'>, <built-in method add of type object at 0x7fc9db52bd40>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': (<function relu at 0x7fc98a30bef0>, <built-in method add of type object at 0x7fc9db52bd40>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': (<built-in method relu of type object at 0x7fc9db52bd40>, <built-in method add of type object at 0x7fc9db52bd40>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': <built-in method add of type object at 0x7fc9db52bd40>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'weight_dtype': torch.qint8,
'bias_dtype': torch.float32,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'num_tensor_args_to_observation_type': {
0: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
1: ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
2: ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
},
{
'pattern': <class 'torch.nn.modules.pooling.AvgPool1d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <built-in method avg_pool1d of type object at 0x7fc9db52bd40>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <class 'torch.nn.modules.pooling.AvgPool2d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <built-in function avg_pool2d>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <class 'torch.nn.modules.pooling.AvgPool3d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <built-in function avg_pool3d>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': (<class 'torch.nn.modules.activation.ReLU'>, <class 'torch.nn.modules.batchnorm.BatchNorm2d'>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'fuser_method': <function reverse_sequential_wrapper2.<locals>.fuser_method at 0x7fc9894c29e0>,
'fused_module': <class 'torch.nn.intrinsic.modules.fused.BNReLU2d'>,
},
{
'pattern': (<function relu at 0x7fc98a30bef0>, <class 'torch.nn.modules.batchnorm.BatchNorm2d'>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'fuser_method': <function reverse_sequential_wrapper2.<locals>.fuser_method at 0x7fc9894c2a70>,
'fused_module': <class 'torch.nn.intrinsic.modules.fused.BNReLU2d'>,
},
{
'pattern': <class 'torch.nn.modules.batchnorm.BatchNorm2d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'observation_type': ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
{
'pattern': (<class 'torch.nn.modules.activation.ReLU'>, <class 'torch.nn.modules.batchnorm.BatchNorm3d'>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'fuser_method': <function reverse_sequential_wrapper2.<locals>.fuser_method at 0x7fc9894c2b00>,
'fused_module': <class 'torch.nn.intrinsic.modules.fused.BNReLU3d'>,
},
{
'pattern': (<function relu at 0x7fc98a30bef0>, <class 'torch.nn.modules.batchnorm.BatchNorm3d'>),
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'fuser_method': <function reverse_sequential_wrapper2.<locals>.fuser_method at 0x7fc9894c2b90>,
'fused_module': <class 'torch.nn.intrinsic.modules.fused.BNReLU3d'>,
},
{
'pattern': <class 'torch.nn.modules.batchnorm.BatchNorm3d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'observation_type': ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
{
'pattern': <class 'torch.nn.intrinsic.modules.fused.BNReLU2d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'observation_type': ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
{
'pattern': <class 'torch.nn.intrinsic.modules.fused.BNReLU3d'>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'observation_type': ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT,
},
{
'pattern': <built-in method cat of type object at 0x7fc9db52bd40>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': <built-in method clamp of type object at 0x7fc9db52bd40>,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': clamp,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
{
'pattern': contiguous,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
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