NIC 536020 Hobby horse Toy Tools, Brown - 536020
Applies a 3D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution"
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Applies element-wise, CELU(x)=max(0,x)+min(0,α∗(exp(x/α)−1))\text{CELU}(x) = \max(0,x) + \min(0, \alpha * (\exp(x/\alpha) - 1))CELU(x)=max(0,x)+min(0,α∗(exp(x/α)−1)).
Drivetrain Chassis: carbon fibre body on spaceframe chassis Gearbox: Powershift 6 speed Automatic Drive: Rear wheel drive
Engine Configuration: Hybrid Straight 4 Location: Mid, longitudinally mounted Displacement: 1,400 cc / 85.4 cu in Valvetrain: 4 valves / cylinder, DOHC Fuel feed: Fuel Injection Aspiration: Turbo Power: 700 bhp / 522 kW @ 9,300 rpm Torque: 490 Nm / 361 ft lbs @ 6,900 rpm BHP/Liter: 500 bhp / liter
Applies 3D average-pooling operation in kT×kH×kWkT \times kH \times kWkT×kH×kW regions by step size sT×sH×sWsT \times sH \times sWsT×sH×sW steps.
Applies element-wise, SELU(x)=scale∗(max(0,x)+min(0,α∗(exp(x)−1)))\text{SELU}(x) = scale * (\max(0,x) + \min(0, \alpha * (\exp(x) - 1)))SELU(x)=scale∗(max(0,x)+min(0,α∗(exp(x)−1))), with α=1.6732632423543772848170429916717\alpha=1.6732632423543772848170429916717α=1.6732632423543772848170429916717 and scale=1.0507009873554804934193349852946scale=1.0507009873554804934193349852946scale=1.0507009873554804934193349852946.
Applies element-wise, Tanh(x)=tanh(x)=exp(x)−exp(−x)exp(x)+exp(−x)\text{Tanh}(x) = \tanh(x) = \frac{\exp(x) - \exp(-x)}{\exp(x) + \exp(-x)}Tanh(x)=tanh(x)=exp(x)+exp(−x)exp(x)−exp(−x)
Applies element-wise the function PReLU(x)=max(0,x)+weight∗min(0,x)\text{PReLU}(x) = \max(0,x) + \text{weight} * \min(0,x)PReLU(x)=max(0,x)+weight∗min(0,x) where weight is a learnable parameter.
When the approximate argument is 'none', it applies element-wise the function GELU(x)=x∗Φ(x)\text{GELU}(x) = x * \Phi(x)GELU(x)=x∗Φ(x)
Applies element-wise, LeakyReLU(x)=max(0,x)+negative_slope∗min(0,x)\text{LeakyReLU}(x) = \max(0, x) + \text{negative\_slope} * \min(0, x)LeakyReLU(x)=max(0,x)+negative_slope∗min(0,x)
Applies a 2D transposed convolution operator over an input image composed of several input planes, sometimes also called "deconvolution".
The torch.nn.attention.bias module contains attention_biases that are designed to be used with scaled_dot_product_attention.
Applies a 1D transposed convolution operator over an input signal composed of several input planes, sometimes also called "deconvolution".
NOTE: yes, it technically is classified as a motorcycle, but the robin was added? that classifies as a motorcycle in the UK, so uh yeah, this should be fine
Applies element-wise, the function Softplus(x)=1β∗log(1+exp(β∗x))\text{Softplus}(x) = \frac{1}{\beta} * \log(1 + \exp(\beta * x))Softplus(x)=β1∗log(1+exp(β∗x)).
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Italian design by Acabion Maranello, British racing and engine competence, German automotive expertise by Acabion Stuttgart, solid US dragster and racing components in a high-tech Hamamatsu originating engine, Swiss manufacturing precision by Acabion Lucerne, Kaizen and lean production expertise by MIKOVA Systems Lucerne, Formula-1 and avionic production standards, three years to build one vehicle in our Lucerne plant. Total GTBO production volume 2007 to 2011 is limited to 26 vehicles.
Applies element-wise LogSigmoid(xi)=log(11+exp(−xi))\text{LogSigmoid}(x_i) = \log \left(\frac{1}{1 + \exp(-x_i)}\right)LogSigmoid(xi)=log(1+exp(−xi)1)
Takes LongTensor with index values of shape (*) and returns a tensor of shape (*, num_classes) that have zeros everywhere except where the index of last dimension matches the corresponding value of the input tensor, in which case it will be 1.
Rearranges elements in a tensor of shape (∗,C×r2,H,W)(*, C \times r^2, H, W)(∗,C×r2,H,W) to a tensor of shape (∗,C,H×r,W×r)(*, C, H \times r, W \times r)(∗,C,H×r,W×r), where r is the upscale_factor.
Reverses the PixelShuffle operation by rearranging elements in a tensor of shape (∗,C,H×r,W×r)(*, C, H \times r, W \times r)(∗,C,H×r,W×r) to a tensor of shape (∗,C×r2,H,W)(*, C \times r^2, H, W)(∗,C×r2,H,W), where r is the downscale_factor.
In-Game Stats Name: Aramain TOGT 4X Top Speed: 370 mph Acceleration: 22.3 Handling: 19.4 Braking: 20 Weight: 0.3 Tonnes Parts: 82 Race Class: X