Restore 58_ConvTranspose3d_LogSumExp_HardSwish_Subtract_Clamp_Max.py

Author: nataliakokoromyti

KernelBench/level2/58_ConvTranspose3d_LogSumExp_HardSwish_Subtract_Clamp_Max.py

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+import torch
+import torch.nn as nn
+
+class Model(nn.Module):
+    """
+    Model that performs a 3D transposed convolution, LogSumExp, HardSwish, subtraction, clamp, and maximum operations.
+    """
+    def __init__(self, in_channels, out_channels, kernel_size, stride, padding, bias_shape):
+        super(Model, self).__init__()
+        self.conv_transpose = nn.ConvTranspose3d(in_channels, out_channels, kernel_size, stride=stride, padding=padding)
+        self.bias = nn.Parameter(torch.randn(bias_shape)) 
+
+    def forward(self, x):
+        x = self.conv_transpose(x)
+        x = torch.logsumexp(x, dim=1, keepdim=True)
+        x = x * torch.sigmoid(x + 3) / 6
+        x = x - self.bias
+        x = torch.clamp(x, min=-1, max=1)
+        x = torch.max(x, dim=1, keepdim=True)[0]
+        return x
+
+batch_size = 128
+in_channels = 3
+out_channels = 16
+depth, height, width = 16, 32, 32
+kernel_size = 3
+stride = 2
+padding = 1
+bias_shape = (out_channels, 1, 1, 1)
+
+def get_inputs():
+    return [torch.randn(batch_size, in_channels, depth, height, width)]
+
+def get_init_inputs():
+    return [in_channels, out_channels, kernel_size, stride, padding, bias_shape]