Fix the incorrect git revision path

seetadet/modeling/efficientnet.py

@@ -16,10 +16,12 @@ from __future__ import print_function
 
 
 import collections
 import collections
 import functools
 import functools
+import math
 
 
 from seetadet.core import registry
 from seetadet.core import registry
 from seetadet.modeling.mobilenet_v3 import conv_triplet
 from seetadet.modeling.mobilenet_v3 import conv_triplet
 from seetadet.modeling.mobilenet_v3 import conv_quintet
 from seetadet.modeling.mobilenet_v3 import conv_quintet
+from seetadet.modeling.mobilenet_v3 import make_divisible
 from seetadet.modules import init
 from seetadet.modules import init
 from seetadet.modules import nn
 from seetadet.modules import nn
 
 
@@ -87,13 +89,26 @@ class InvertedResidual(nn.Module):
 class NASMobileNet(nn.Module):
 class NASMobileNet(nn.Module):
     """NAS variant of mobilenet class."""
     """NAS variant of mobilenet class."""
 
 
-    def __init__(self, arch, preset):
+    def __init__(self, arch, preset, width_mult=1.0, depth_mult=1.0):
         super(NASMobileNet, self).__init__()
         super(NASMobileNet, self).__init__()
         # Hand-craft configurations.
         # Hand-craft configurations.
         repeats, strides, out_channels, def_blocks = preset
         repeats, strides, out_channels, def_blocks = preset
         assert sum(repeats) == len(arch), 'Bad architecture.'
         assert sum(repeats) == len(arch), 'Bad architecture.'
         self.feature_dims = collections.OrderedDict()
         self.feature_dims = collections.OrderedDict()
 
 
+        # Apply the width scaling.
+        out_channels = list(map(lambda x: make_divisible(x * width_mult),
+                                out_channels))
+
+        # Apply the depth scaling.
+        repeated_arch = []
+        for i, repeat in enumerate(repeats):
+            idx_start = sum(repeats[:i])
+            indices = arch[idx_start: idx_start + repeat]
+            repeat = int(math.ceil(repeat * depth_mult))
+            repeated_arch += (indices + [indices[-1]] * (repeat - len(indices)))
+        arch = repeated_arch
+
         # Stem.
         # Stem.
         features = [nn.Sequential(
         features = [nn.Sequential(
             *conv_triplet(
             *conv_triplet(
@@ -108,6 +123,7 @@ class NASMobileNet(nn.Module):
         dim_in, stride_out = out_channels[0], 2
         dim_in, stride_out = out_channels[0], 2
         for repeat, dim_out, stride in \
         for repeat, dim_out, stride in \
                 zip(repeats, out_channels[1:], strides):
                 zip(repeats, out_channels[1:], strides):
+            repeat = int(math.ceil(repeat * depth_mult))
             stride_out *= stride
             stride_out *= stride
             for i in range(repeat):
             for i in range(repeat):
                 stride = stride if i == 0 else 1
                 stride = stride if i == 0 else 1
@@ -169,12 +185,49 @@ class ModelSetting(object):
     )
     )
 
 
 
 
-@registry.backbone.register('efficient_b0')
-def efficient_b0():
+def efficientnet(width_mult=1.0, depth_mult=1.0):
     return NASMobileNet([10301,
     return NASMobileNet([10301,
                          60301, 60301,
                          60301, 60301,
                          60501, 60501,
                          60501, 60501,
                          60301, 60301, 60301,
                          60301, 60301, 60301,
                          60501, 60501, 60501,
                          60501, 60501, 60501,
                          60501, 60501, 60501, 60501,
                          60501, 60501, 60501, 60501,
-                         60301], ModelSetting.EFFICIENT)
+                         60301],
+                        preset=ModelSetting.EFFICIENT,
+                        width_mult=width_mult,
+                        depth_mult=depth_mult)
+
+
+@registry.backbone.register('efficientnet_b0')
+def efficientnet_b0():
+    return efficientnet(width_mult=1.0, depth_mult=1.0)
+
+
+@registry.backbone.register('efficientnet_b1')
+def efficientnet_b1():
+    return efficientnet(width_mult=1.0, depth_mult=1.1)
+
+
+@registry.backbone.register('efficientnet_b2')
+def efficientnet_b2():
+    return efficientnet(width_mult=1.1, depth_mult=1.2)
+
+
+@registry.backbone.register('efficientnet_b3')
+def efficientnet_b3():
+    return efficientnet(width_mult=1.2, depth_mult=1.4)
+
+
+@registry.backbone.register('efficientnet_b4')
+def efficientnet_b4():
+    return efficientnet(width_mult=1.4, depth_mult=1.8)
+
+
+@registry.backbone.register('efficientnet_b5')
+def efficientnet_b5():
+    return efficientnet(width_mult=1.6, depth_mult=2.2)
+
+
+@registry.backbone.register('efficientnet_b6')
+def efficientnet_b6():
+    return efficientnet(width_mult=1.8, depth_mult=2.6)

seetadet/modeling/mobilenet_v2.py

@@ -23,6 +23,15 @@ from seetadet.modules import init
 from seetadet.modules import nn
 from seetadet.modules import nn
 
 
 
 
+def make_divisible(v, divisor=8):
+    """Return the divisible value."""
+    min_value = divisor
+    new_v = max(min_value, int(v + divisor / 2) // divisor * divisor)
+    if new_v < 0.9 * v:
+        new_v += divisor
+    return new_v
+
+
 def conv_triplet(dim_in, dim_out, kernel_size=1, stride=1):
 def conv_triplet(dim_in, dim_out, kernel_size=1, stride=1):
     """Return a convolution triplet."""
     """Return a convolution triplet."""
     return [nn.Conv2d(dim_in, dim_out,
     return [nn.Conv2d(dim_in, dim_out,
@@ -78,13 +87,17 @@ class InvertedResidual(nn.Module):
 class NASMobileNet(nn.Module):
 class NASMobileNet(nn.Module):
     """NAS variant of mobilenet class."""
     """NAS variant of mobilenet class."""
 
 
-    def __init__(self, arch, preset):
+    def __init__(self, arch, preset, width_mult=1.0):
         super(NASMobileNet, self).__init__()
         super(NASMobileNet, self).__init__()
         # Hand-craft configurations
         # Hand-craft configurations
         repeats, strides, out_channels, def_blocks = preset
         repeats, strides, out_channels, def_blocks = preset
         assert sum(repeats) == len(arch), 'Bad architecture.'
         assert sum(repeats) == len(arch), 'Bad architecture.'
         self.feature_dims = collections.OrderedDict()
         self.feature_dims = collections.OrderedDict()
 
 
+        # Apply the width scaling.
+        out_channels = list(map(lambda x: make_divisible(x * width_mult),
+                                out_channels))
+
         # Stem.
         # Stem.
         features = [nn.Sequential(
         features = [nn.Sequential(
             *conv_triplet(
             *conv_triplet(

seetadet/modeling/mobilenet_v3.py

@@ -73,7 +73,6 @@ class SqueezeExcite(nn.Module):
     def __init__(self, dim_in, squeeze_ratio=0.25):
     def __init__(self, dim_in, squeeze_ratio=0.25):
         super(SqueezeExcite, self).__init__()
         super(SqueezeExcite, self).__init__()
         dim = make_divisible(dim_in * squeeze_ratio)
         dim = make_divisible(dim_in * squeeze_ratio)
-        print(dim)
         self.layers = nn.Sequential(nn.AvgPool2d(-1, global_pooling=True),
         self.layers = nn.Sequential(nn.AvgPool2d(-1, global_pooling=True),
                                     nn.Conv2d(dim_in, dim, kernel_size=1),
                                     nn.Conv2d(dim_in, dim, kernel_size=1),
                                     nn.ReLU(True),
                                     nn.ReLU(True),
@@ -129,15 +128,19 @@ class InvertedResidual(nn.Module):
 
 
 
 
 class NASMobileNet(nn.Module):
 class NASMobileNet(nn.Module):
-    """The NAS variant of mobilenet class."""
+    """NAS variant of mobilenet class."""
 
 
-    def __init__(self, arch, preset):
+    def __init__(self, arch, preset, width_mult=1.0):
         super(NASMobileNet, self).__init__()
         super(NASMobileNet, self).__init__()
         # Hand-craft configurations.
         # Hand-craft configurations.
         repeats, strides, out_channels, def_blocks = preset
         repeats, strides, out_channels, def_blocks = preset
         assert sum(repeats) == len(arch), 'Bad architecture.'
         assert sum(repeats) == len(arch), 'Bad architecture.'
         self.feature_dims = collections.OrderedDict()
         self.feature_dims = collections.OrderedDict()
 
 
+        # Apply the width scaling.
+        out_channels = list(map(lambda x: make_divisible(x * width_mult),
+                                out_channels))
+
         # Stem.
         # Stem.
         features = [nn.Sequential(
         features = [nn.Sequential(
             *conv_triplet(
             *conv_triplet(

setup.py

@@ -26,7 +26,7 @@ with open('version.txt', 'r') as f:
     version = f.read().strip()
     version = f.read().strip()
 try:
 try:
     git_version = subprocess.check_output(
     git_version = subprocess.check_output(
-        ['git', 'rev-parse', 'HEAD'], cwd='../').decode('ascii').strip()
+        ['git', 'rev-parse', 'HEAD'], cwd='./').decode('ascii').strip()
 except (OSError, subprocess.CalledProcessError):
 except (OSError, subprocess.CalledProcessError):
     git_version = None
     git_version = None