Initial import: grid-bot — grid trading bot for BTC-USDT on Cifra Markets
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#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)
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#pragma once
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#include <ATen/EmptyTensor.h>
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#include <ATen/Formatting.h>
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#include <ATen/core/ATenGeneral.h>
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#include <ATen/core/Generator.h>
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#include <c10/core/ScalarType.h>
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#include <c10/core/StorageImpl.h>
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#include <c10/core/UndefinedTensorImpl.h>
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#include <c10/util/ArrayRef.h>
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#include <c10/util/Exception.h>
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#include <c10/util/accumulate.h>
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#include <c10/util/irange.h>
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#include <algorithm>
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#define AT_DISALLOW_COPY_AND_ASSIGN(TypeName) \
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TypeName(const TypeName&) = delete; \
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void operator=(const TypeName&) = delete
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namespace at {
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TORCH_API int _crash_if_asan(int /*arg*/);
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// Converts a TensorList (i.e. ArrayRef<Tensor> to vector of TensorImpl*)
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// NB: This is ONLY used by legacy TH bindings, and ONLY used by cat.
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// Once cat is ported entirely to ATen this can be deleted!
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inline std::vector<TensorImpl*> checked_dense_tensor_list_unwrap(
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ArrayRef<Tensor> tensors,
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const char* name,
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int pos,
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c10::DeviceType device_type,
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ScalarType scalar_type) {
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std::vector<TensorImpl*> unwrapped;
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unwrapped.reserve(tensors.size());
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for (const auto i : c10::irange(tensors.size())) {
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const auto& expr = tensors[i];
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if (expr.layout() != Layout::Strided) {
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TORCH_CHECK(
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false,
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"Expected dense tensor but got ",
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expr.layout(),
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" for sequence element ",
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i,
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" in sequence argument at position #",
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pos,
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" '",
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name,
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"'");
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}
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if (expr.device().type() != device_type) {
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TORCH_CHECK(
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false,
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"Expected object of device type ",
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device_type,
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" but got device type ",
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expr.device().type(),
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" for sequence element ",
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i,
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" in sequence argument at position #",
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pos,
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" '",
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name,
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"'");
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}
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if (expr.scalar_type() != scalar_type) {
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TORCH_CHECK(
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false,
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"Expected object of scalar type ",
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scalar_type,
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" but got scalar type ",
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expr.scalar_type(),
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" for sequence element ",
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i,
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" in sequence argument at position #",
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pos,
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" '",
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name,
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"'");
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}
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unwrapped.emplace_back(expr.unsafeGetTensorImpl());
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}
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return unwrapped;
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}
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template <size_t N>
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std::array<int64_t, N> check_intlist(
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ArrayRef<int64_t> list,
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const char* name,
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int pos) {
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if (list.empty()) {
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// TODO: is this necessary? We used to treat nullptr-vs-not in IntList
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// differently with strides as a way of faking optional.
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list = {};
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}
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auto res = std::array<int64_t, N>();
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if (list.size() == 1 && N > 1) {
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res.fill(list[0]);
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return res;
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}
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if (list.size() != N) {
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TORCH_CHECK(
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false,
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"Expected a list of ",
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N,
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" ints but got ",
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list.size(),
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" for argument #",
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pos,
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" '",
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name,
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"'");
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}
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std::copy_n(list.begin(), N, res.begin());
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return res;
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}
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using at::detail::check_size_nonnegative;
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namespace detail {
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template <typename T>
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TORCH_API Tensor tensor_cpu(ArrayRef<T> values, const TensorOptions& options);
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template <typename T>
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TORCH_API Tensor
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tensor_backend(ArrayRef<T> values, const TensorOptions& options);
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template <typename T>
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TORCH_API Tensor
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tensor_complex_cpu(ArrayRef<T> values, const TensorOptions& options);
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template <typename T>
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TORCH_API Tensor
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tensor_complex_backend(ArrayRef<T> values, const TensorOptions& options);
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} // namespace detail
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} // namespace at
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#else
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#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined."
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#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)
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