{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"ds-1000","formal_name":"DS-1000","introduction":"DS-1000 builds 1,000 data-science problems from real StackOverflow questions across seven libraries including NumPy, Pandas and Matplotlib. The problems are perturbed so that recalling the original answer does not solve them.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://ds1000-code-gen.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"fef2567a-ce2e-55ac-9f97-bee811f7d212","task_key":"default--test--695","task_revision_id":"1","upstream_id":"695","short_description":"I'm using tensorflow 2.10.0.","config":"default","split":"test","body":"{\"library\":\"Tensorflow\",\"prompt\":\"Problem:\\nI'm using tensorflow 2.10.0.\\nI have two 3D tensors, tensor A which has shape [B,N,S] and tensor B which also has shape [B,N,S]. What I want to get is a third tensor C, which I expect to have [B,N,N] shape, where the element C[i,j,k] = np.dot(A[i,j,:], B[i,k,:]. I also want to achieve this is a vectorized way.\\nSome further info: The two tensors A and B have shape [Batch_size, Num_vectors, Vector_size]. The tensor C, is supposed to represent the dot product between each element in the batch from A and each element in the batch from B, between all of the different vectors.\\nHope that it is clear enough and looking forward to you answers!\\n\\nA:\\n<code>\\nimport tensorflow as tf\\nimport numpy as np\\n\\nnp.random.seed(10)\\nA = tf.constant(np.random.randint(low=0, high=5, size=(10, 20, 30)))\\nB = tf.constant(np.random.randint(low=0, high=5, size=(10, 20, 30)))\\n</code>\\nresult = ... # put solution in this variable\\nBEGIN SOLUTION\\n<code>\\n\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://ds1000-code-gen.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}