Add Single-Path NAS pixel1 model

models/genmobilenet.py

@@ -5,6 +5,7 @@ A generic MobileNet class with building blocks to support a variety of models:
 * MobileNetV2
 * FBNet-C (TODO A & B)
 * ChamNet (TODO still guessing at architecture definition)
+* Single-Path NAS Pixel1
 * ShuffleNetV2 (TODO add IR shuffle block)
 * And likely more...
 
@@ -25,8 +26,9 @@ from models.adaptive_avgmax_pool import SelectAdaptivePool2d
 from data.transforms import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 __all__ = ['GenMobileNet', 'mnasnet0_50', 'mnasnet0_75', 'mnasnet1_00', 'mnasnet1_40',
-           'semnasnet0_50', 'semnasnet0_75', 'semnasnet1_00', 'semnasnet1_40',
+           'semnasnet0_50', 'semnasnet0_75', 'semnasnet1_00', 'semnasnet1_40', 'mnasnet_small',
-           'mnasnet_small']
+           'mobilenetv1_1_00', 'mobilenetv2_1_00', 'chamnetv1_1_00', 'chamnetv2_1_00',
+           'fbnetc_1_00', 'spnasnet1_00']
 
 
 def _cfg(url='', **kwargs):
@@ -54,6 +56,7 @@ default_cfgs = {
     'chamnetv1_1_00': _cfg(url=''),
     'chamnetv2_1_00': _cfg(url=''),
     'fbnetc_1_00': _cfg(url=''),
+    'spnasnet1_00': _cfg(url=''),
 }
 
 _DEBUG = True
@@ -476,6 +479,7 @@ class GenMobileNet(nn.Module):
       * MNASNet A1, B1, and small
       * FBNet A, B, and C
       * ChamNet (arch details are murky)
+      * Single-Path NAS Pixel1
     """
 
     def __init__(self, block_args, num_classes=1000, in_chans=3, stem_size=32, num_features=1280,
@@ -820,6 +824,45 @@ def _gen_fbnetc(depth_multiplier, num_classes=1000, **kwargs):
     return model
 
 
+def _gen_spnasnet(depth_multiplier, num_classes=1000, **kwargs):
+    """Creates the Single-Path NAS model from search targeted for Pixel1 phone.
+
+    Paper: https://arxiv.org/abs/1904.02877
+
+    Args:
+      depth_multiplier: multiplier to number of channels per layer.
+    """
+    arch_def = [
+        # stage 0, 112x112 in
+        ['ds_r1_k3_s1_c16_noskip'],
+        # stage 1, 112x112 in
+        ['ir_r3_k3_s2_e3_c24'],
+        # stage 2, 56x56 in
+        ['ir_r1_k5_s2_e6_c40', 'ir_r3_k3_s1_e3_c40'],
+        # stage 3, 28x28 in
+        ['ir_r1_k5_s2_e6_c80', 'ir_r3_k3_s1_e3_c80'],
+        # stage 4, 14x14in
+        ['ir_r1_k5_s1_e6_c96', 'ir_r3_k5_s1_e3_c96'],
+        # stage 5, 14x14in
+        ['ir_r4_k5_s2_e6_c192'],
+        # stage 6, 7x7 in
+        ['ir_r1_k3_s1_e6_c320_noskip']
+    ]
+    bn_momentum, bn_eps = _resolve_bn_params(kwargs)
+    model = GenMobileNet(
+        arch_def,
+        num_classes=num_classes,
+        stem_size=32,
+        depth_multiplier=depth_multiplier,
+        depth_divisor=8,
+        min_depth=None,
+        bn_momentum=bn_momentum,
+        bn_eps=bn_eps,
+        **kwargs
+    )
+    return model
+
+
 def mnasnet0_50(num_classes=1000, in_chans=3, pretrained=False, **kwargs):
     """ MNASNet B1, depth multiplier of 0.5. """
     default_cfg = default_cfgs['mnasnet0_50']
@@ -958,3 +1001,13 @@ def chamnetv2_1_00(num_classes, in_chans=3, pretrained=False, **kwargs):
     if pretrained:
         load_pretrained(model, default_cfg, num_classes, in_chans)
     return model
+
+
+def spnasnet1_00(num_classes, in_chans=3, pretrained=False, **kwargs):
+    """ Single-Path NAS Pixel1"""
+    default_cfg = default_cfgs['spnasnet1_00']
+    model = _gen_spnasnet(1.0, num_classes=num_classes, in_chans=in_chans, **kwargs)
+    model.default_cfg = default_cfg
+    if pretrained:
+        load_pretrained(model, default_cfg, num_classes, in_chans)
+    return model

models/model_factory.py

@@ -11,7 +11,8 @@ from models.pnasnet import pnasnet5large
 from models.genmobilenet import \
     mnasnet0_50, mnasnet0_75, mnasnet1_00, mnasnet1_40,\
     semnasnet0_50, semnasnet0_75, semnasnet1_00, semnasnet1_40, mnasnet_small,\
-    mobilenetv1_1_00, mobilenetv2_1_00, fbnetc_1_00, chamnetv1_1_00, chamnetv2_1_00
+    mobilenetv1_1_00, mobilenetv2_1_00, fbnetc_1_00, chamnetv1_1_00, chamnetv2_1_00,\
+    spnasnet1_00
 
 from models.helpers import load_checkpoint