docs: Update op support list

Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]>

Author: narendasan

docs/v0.2.0/_notebooks/Resnet50-example.html

@@ -690,7 +690,7 @@
         </div>
        </div>
        <p>
-        <img alt="b78d781b37a9419a818aff2f2cac6056" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="09a03bf1bb8e4e44b23f950611bff8c0" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
        </p>
        <h1 id="notebooks-resnet50-example--page-root">
         TRTorch Getting Started - ResNet 50

docs/v0.2.0/_notebooks/lenet-getting-started.html

@@ -784,7 +784,7 @@
         </div>
        </div>
        <p>
-        <img alt="be77293abe074c06af666073aefc5d7c" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="4a8a1d2302d2486c8b5002d12020eb54" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
        </p>
        <h1 id="notebooks-lenet-getting-started--page-root">
         TRTorch Getting Started - LeNet

docs/v0.2.0/_notebooks/ssd-object-detection-demo.html

@@ -804,7 +804,7 @@
         </div>
        </div>
        <p>
-        <img alt="a6ddbb83c13c433dbf239cdbe55afcd9" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
+        <img alt="b30ba4b8d3184e6495c9a21eb7c87584" src="http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png"/>
        </p>
        <h1 id="notebooks-ssd-object-detection-demo--page-root">
         Object Detection with TRTorch (SSD)

docs/v0.2.0/_sources/indices/supported_ops.rst.txt

@@ -35,6 +35,7 @@ Operators Currently Supported Through Converters
 - aten::div.Tensor(Tensor self, Tensor other) -> (Tensor)
 - aten::div_.Scalar(Tensor(a!) self, Scalar other) -> (Tensor(a!))
 - aten::div_.Tensor(Tensor(a!) self, Tensor other) -> (Tensor(a!))
+- aten::elu(Tensor self, Scalar alpha=1, Scalar scale=1, Scalar input_scale=1) -> (Tensor)
 - aten::embedding(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> (Tensor)
 - aten::eq.Scalar(Tensor self, Scalar other) -> (Tensor)
 - aten::eq.Tensor(Tensor self, Tensor other) -> (Tensor)
@@ -71,6 +72,7 @@ Operators Currently Supported Through Converters
 - aten::mean.dim(Tensor self, int[] dim, bool keepdim=False, *, int? dtype=None) -> (Tensor)
 - aten::min(Tensor self) -> (Tensor)
 - aten::min.other(Tensor self, Tensor other) -> (Tensor)
+- aten::mul.Scalar(Tensor self, Scalar other) -> (Tensor)
 - aten::mul.Tensor(Tensor self, Tensor other) -> (Tensor)
 - aten::mul_.Tensor(Tensor(a!) self, Tensor other) -> (Tensor(a!))
 - aten::narrow(Tensor(a) self, int dim, int start, int length) -> (Tensor(a))
@@ -112,6 +114,7 @@ Operators Currently Supported Through Converters
 - aten::tanh(Tensor input) -> (Tensor)
 - aten::tanh_(Tensor(a!) self) -> (Tensor(a!))
 - aten::topk(Tensor self, int k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)
+- aten::transpose.int(Tensor(a) self, int dim0, int dim1) -> (Tensor(a))
 - aten::unsqueeze(Tensor(a) self, int dim) -> (Tensor(a))
 - aten::upsample_bilinear2d(Tensor self, int[2] output_size, bool align_corners, float? scales_h=None, float? scales_w=None) -> (Tensor)
 - aten::upsample_bilinear2d.vec(Tensor input, int[]? output_size, bool align_corners, float[]? scale_factors) -> (Tensor)