From 5eca742f6c0e513d8c7d8085fd14b7a754ea96f7 Mon Sep 17 00:00:00 2001 From: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Date: Fri, 10 Dec 2021 16:02:48 -0500 Subject: [PATCH] Fix special character in MDX (#14721) --- docs/source/quicktour.mdx | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/source/quicktour.mdx b/docs/source/quicktour.mdx index 7c2862c74e..f3e5c7f2fa 100644 --- a/docs/source/quicktour.mdx +++ b/docs/source/quicktour.mdx @@ -246,10 +246,10 @@ objects are described in greater detail [here](main_classes/output). For now, le ```py >>> print(pt_outputs) SequenceClassifierOutput(loss=None, logits=tensor([[-4.0833, 4.3364], - [ 0.0818, -0.0418]], grad_fn=&lt;AddmmBackward>), hidden_states=None, attentions=None) + [ 0.0818, -0.0418]], grad_fn=), hidden_states=None, attentions=None) ===PT-TF-SPLIT=== >>> print(tf_outputs) -TFSequenceClassifierOutput(loss=None, logits=&lt;tf.Tensor: shape=(2, 2), dtype=float32, numpy= +TFSequenceClassifierOutput(loss=None, logits=, hidden_states=None, attentions=None) ``` @@ -278,7 +278,7 @@ We can see we get the numbers from before: ```py >>> print(pt_predictions) tensor([[2.2043e-04, 9.9978e-01], - [5.3086e-01, 4.6914e-01]], grad_fn=&lt;SoftmaxBackward>) + [5.3086e-01, 4.6914e-01]], grad_fn=) ===PT-TF-SPLIT=== >>> print(tf_predictions) tf.Tensor( @@ -293,13 +293,13 @@ attribute: >>> import torch >>> pt_outputs = pt_model(**pt_batch, labels = torch.tensor([1, 0])) >>> print(pt_outputs) -SequenceClassifierOutput(loss=tensor(0.3167, grad_fn=&lt;NllLossBackward>), logits=tensor([[-4.0833, 4.3364], - [ 0.0818, -0.0418]], grad_fn=&lt;AddmmBackward>), hidden_states=None, attentions=None) +SequenceClassifierOutput(loss=tensor(0.3167, grad_fn=), logits=tensor([[-4.0833, 4.3364], + [ 0.0818, -0.0418]], grad_fn=), hidden_states=None, attentions=None) ===PT-TF-SPLIT=== >>> import tensorflow as tf >>> tf_outputs = tf_model(tf_batch, labels = tf.constant([1, 0])) >>> print(tf_outputs) -TFSequenceClassifierOutput(loss=&lt;tf.Tensor: shape=(2,), dtype=float32, numpy=array([2.2051e-04, 6.3326e-01], dtype=float32)>, logits=&lt;tf.Tensor: shape=(2, 2), dtype=float32, numpy= +TFSequenceClassifierOutput(loss=, logits=, hidden_states=None, attentions=None) ```