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Results 21 - 30 of 45 for dimensioner (0.11 sec)
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tensorflow/c/c_api_experimental_test.cc
/*input_shapes*/ {make_shape({3, 2}), unknown_shape()}, /*input_tensors*/ {}, /*expected_shape*/ make_shape({3, kUnknownDim})); // Infer shape when some dimensions are unknown. CheckOutputShapes( matmul_op, /*input_shapes*/ {make_shape({kUnknownDim, 2}), make_shape({2, 4})}, /*input_tensors*/ {}, /*expected_shape*/ make_shape({kUnknownDim, 4}));
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Tue Jan 17 22:27:52 UTC 2023 - 13.1K bytes - Viewed (0) -
RELEASE.md
control flow. * Add `RaggedTensor.numpy()`. * Update `RaggedTensor.__getitem__` to preserve uniform dimensions & allow indexing into uniform dimensions. * Update `tf.expand_dims` to always insert the new dimension as a non-ragged dimension. * Update `tf.embedding_lookup` to use `partition_strategy` and `max_norm` when `ids` is ragged.
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Tue Oct 22 14:33:53 UTC 2024 - 735.3K bytes - Viewed (0) -
src/main/webapp/js/bootstrap.min.js.map
$(this._element)\n .removeClass(ClassName.COLLAPSING)\n .addClass(ClassName.COLLAPSE)\n .addClass(ClassName.SHOW)\n\n this._element.style[dimension] = ''\n\n this.setTransitioning(false)\n\n $(this._element).trigger(Event.SHOWN)\n }\n\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1)\n const scrollSize = `scroll${capitalizedDimension}`\n const transitionDuration = Util.getTransitionDurationFromElement(this._element)\n\n $(this._element)\n...
Registered: Thu Oct 31 13:40:30 UTC 2024 - Last Modified: Sat Jan 11 06:54:28 UTC 2020 - 189.9K bytes - Viewed (0) -
android/guava/src/com/google/common/collect/ArrayTable.java
import java.util.Map; import java.util.Set; import javax.annotation.CheckForNull; import org.checkerframework.checker.nullness.qual.Nullable; /** * Fixed-size {@link Table} implementation backed by a two-dimensional array. * * <p><b>Warning:</b> {@code ArrayTable} is rarely the {@link Table} implementation you want. First, * it requires that the complete universe of rows and columns be specified at construction time.
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Wed Oct 30 16:15:19 UTC 2024 - 26.3K bytes - Viewed (0) -
tensorflow/c/eager/dlpack.cc
bool valid = true; int64_t expected_stride = 1; for (int i = ndim - 1; i >= 0; --i) { // Empty tensors are always compact regardless of strides. if (shape_arr[i] == 0) return true; // Note that dimensions with size=1 can have any stride. if (shape_arr[i] != 1 && stride_arr[i] != expected_stride) { valid = false; } expected_stride *= shape_arr[i]; } return valid; } } // namespace
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 05:11:17 UTC 2024 - 12.9K bytes - Viewed (0) -
src/main/webapp/js/admin/bootstrap.min.js.map
$(this._element)\n .removeClass(CLASS_NAME_COLLAPSING)\n .addClass(`${CLASS_NAME_COLLAPSE} ${CLASS_NAME_SHOW}`)\n\n this._element.style[dimension] = ''\n\n this.setTransitioning(false)\n\n $(this._element).trigger(EVENT_SHOWN)\n }\n\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1)\n const scrollSize = `scroll${capitalizedDimension}`\n const transitionDuration = Util.getTransitionDurationFromElement(this._element)\n\n $(this._element)\n...
Registered: Thu Oct 31 13:40:30 UTC 2024 - Last Modified: Sat Oct 26 01:49:09 UTC 2024 - 180.9K bytes - Viewed (0) -
guava/src/com/google/common/util/concurrent/SmoothRateLimiter.java
* example is when a server has just booted, and it is mostly busy with getting itself up to * speed). * * To deal with such scenarios, we add an extra dimension, that of "past underutilization", * modeled by "storedPermits" variable. This variable is zero when there is no underutilization, * and it can grow up to maxStoredPermits, for sufficiently large underutilization. So, the
Registered: Fri Nov 01 12:43:10 UTC 2024 - Last Modified: Tue Apr 04 09:45:04 UTC 2023 - 19.3K bytes - Viewed (0) -
tensorflow/c/c_api_experimental.cc
DCHECK(index >= 0 && index < shape_list->num_items); TF_ShapeAndType& shape = shape_list->items[index]; DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!"; DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!"; shape.num_dims = num_dims; shape.dims = new int64_t[num_dims]; memcpy(shape.dims, dims, sizeof(int64_t) * num_dims); }
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 16:27:48 UTC 2024 - 29.5K bytes - Viewed (0) -
tensorflow/c/c_api_test.cc
// Fetch the shape and validate it is 2 by -1. num_dims = TF_GraphGetTensorNumDims(graph, feed_out_0, s); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); EXPECT_EQ(2, num_dims); // Resize the dimension vector appropriately. int64_t returned_dims[2]; TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); EXPECT_EQ(dims[0], returned_dims[0]);
Registered: Tue Nov 05 12:39:12 UTC 2024 - Last Modified: Sat Oct 12 16:27:48 UTC 2024 - 97K bytes - Viewed (0) -
src/main/webapp/js/admin/plugins/form-validator/jquery.form-validator.min.js
",groupCheckedTooFewStart:"Please choose at least ",groupCheckedTooManyStart:"Please choose a maximum of ",groupCheckedEnd:" item(s)",badCreditCard:"The credit card number is not correct",badCVV:"The CVV number was not correct",wrongFileDim:"Incorrect image dimensions,",imageTooTall:"the image can not be taller than",imageTooWide:"the image can not be wider than",imageTooSmall:"the image was too small",min:"min",max:"max",imageRatioNotAccepted:"Image ratio is not be accepted",badBrazilTelephoneAnswer:"The phone...
Registered: Thu Oct 31 13:40:30 UTC 2024 - Last Modified: Mon Jan 01 05:12:47 UTC 2018 - 32.8K bytes - Viewed (0)